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Messages - Imrul Hasan Tusher

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16
Robotics / FLYING CAR LEADERS: ARCHER & JOBY AVIATION
« on: April 15, 2024, 03:36:36 PM »
FLYING CAR LEADERS: ARCHER & JOBY AVIATION


Flying cars are finally here.

You can call them “eVTOLs” (electric vertical take-off/landing) or “air taxis,” I personally will call them flying cars.

After decades of waiting, the convergence of a few key technologies and factors will enable commercial service to start in 2025:

DEP or direct electric propulsion: special electric motors

Batteries: higher energy density, cheaper batteries, mainly driven by Tesla

Materials: lightweight, strong materials

Sensors: a new generation of sensors

Computation/AI: the ability to integrate all data for safe flights

Regulatory Support: governments are finally ready to license this tech

Regarding this last bullet, in November 2022 the US Federal Aviation Administration (FAA) proposed new rules that help pave the way for commercial air taxi operations by 2025, adding something called “powered-lift” operations to its regulations.

Former acting FAA Administrator Billy Nolen has said this about the future timeline:

“We know that when the Los Angeles Olympics get underway in 2028, air taxis will be in high demand. We may see some of them in the years leading up, but nowhere near the scale in 2028.”

Industry reports suggest the potential for a $30 billion marketplace by 2030.

In today’s blog, we’ll look at the two leading flying car companies: Archer Aviation and Joby Aviation.

Let’s dive in…

Archer Aviation

Last month, I hosted Archer Aviation CEO Adam Goldstein and Chief Commercial Officer Nikhil Goel at the Abundance Summit.

In September of 2021, Archer Aviation went public (via SPAC) for $3.8 billion.

Today, their flying car design called Midnight boasts an impressive performance envelope:

Payload: Pilot + 4 paying passengers + luggage

Propulsion: 12 electric engines supported by 6 independent battery packs

Range: Up to 100 miles

Speed: Up to 150 miles per hour

Altitude: Typically, 1,500 feet (below 5,000 feet)

Charge time: 12-minute charge time between back-to-back 20-mile flights

The year 2023 marked a pivotal milestone in the development of Midnight, as the company conducted its first full-scale, uncrewed, and tethered test flight. This achievement, the result of four years of rigorous flight testing, paved the way for further advancements.

Looking ahead, Archer is poised to conduct an astounding 400 tests of its Midnight aircraft in 2024, a testament to their unwavering dedication to perfecting this groundbreaking technology.

On the regulatory front, Archer has made significant strides. The Federal Aviation Administration (FAA) has recently approved certification plans for Archer's production aircraft, and the company has announced that the first three piloted aircraft are currently under construction. These conforming Midnight aircraft will begin piloted flight testing later this year and will subsequently undergo “for credit” flight testing with the FAA as Archer progresses towards commercialization.

The company has secured an impressive indicative order book of up to 700 aircraft, valued at $3.5 billion, from major players such as United Airlines in the US, InterGlobe in India, and Air Chateau in the United Arab Emirates.

So, when can we expect to see Archer's Midnight overhead?

The company has set an ambitious goal of bringing the Midnight eVTOL to market by 2025. In partnership with Atlantic Aviation, Archer is developing electric aircraft infrastructure at existing assets, including Santa Monica Municipal Airport (SMO). Early launch markets will focus on highly congested cities such as Los Angeles, New York, and Miami, with initial routes connecting airports to city centers. As availability of the Midnight increases, services will expand to other locations across Atlantic's portfolio.

To illustrate the transformative potential of eVTOL technology, consider a trip from Santa Monica to Malibu. While this 12-mile journey could take over an hour by road, an air taxi would cover the distance in a mere five minutes, with each passenger paying roughly $30 to $40—less than the cost of a rideshare vehicle.

Joby Aviation

Founded 14 years ago, Joby was the first serious flying car company, and the first to go public in August of 2021 for $4.5 billion. And, even more impressive, in 2022, Joby distinguished itself as the first eVTOL firm to receive US airworthiness certification—a notable badge of honor in a burgeoning industry.

Among the main investors bolstering Joby's successes are Delta Air Lines and the automotive giant Toyota (which has actively aided the air taxi manufacturer in its plans to erect a factory in Ohio).

Here are the details of Joby’s eVTOL performance:

Payload: Pilot + 4 paying passengers + luggage (total capacity of 1,000 lbs.)
Propulsion: 6 electric dual-wound motors on 6 tilt-prop propellers
Range: Up to 150 miles
Speed: Up to 205 miles per hour
Altitude: Typically, 1,500 feet (below 5,000 feet)
In September 2023, Joby signed a significant contract with the US Air Force, valued at up to $131 million, and delivered its first eVTOL to Edwards Air Force Base in Southern California. This partnership involves collaboration with NASA to research the aircraft's performance in urban environments, providing valuable insights for air taxi development and the FAA.

Joby recently announced plans for a $500 million manufacturing plant in Ohio, set to begin construction in 2024, with the capacity to produce up to 500 aircraft annually.

CEO JoeBen Bevirt envisions Joby's eVTOLs as an integral part of aerial ridesharing networks by 2025. This vision took a significant step forward in November 2023 when Joby conducted the first eVTOL test flights in New York City. Furthermore, in February 2024, the company secured an exclusive six-year deal to operate air taxis in Dubai, with commercial operations expected to begin by early 2026.

The skies above are about to get a lot more interesting.

Why This Matters

Flying cars promise to redefine not just transportation, but also our very perception of accessibility and proximity.

As Archer gears up to manufacture 2,000 Midnight vehicles per year, and Joby exceeds 500 eVTOLs per year, the total production rate of flying cars will rival the production of all other flying aircraft put together.

We are poised to embrace a world where the distant becomes near, the inaccessible becomes reachable, and where time, traditionally lost in transit, is reclaimed.

Another benefit of eVTOLs will be an expansion of human connection and interaction. Communities once isolated by geographical challenges will now become integral parts of urban tapestries.

The age-old dichotomy of urban hustle and rural tranquility may very well converge, creating a harmonious blend of both worlds. As eVTOL technology continues its ascent, we are not just witnessing the evolution of travel; we are partaking in a holistic transformation of human experience.

Source: https://www.diamandis.com/blog/abundance-48-flying-car-leaders-archer-joby


17
Generative AI / AI Coding Is Going From Copilot to Autopilot
« on: April 15, 2024, 02:52:26 PM »
AI Coding Is Going From Copilot to Autopilot


ANDRIY ONUFRIYENKO/GETTY IMAGES

A new breed of AI-powered coding tools have emerged—and they’re claiming to be more autonomous versions of earlier assistants like GitHub Copilot, Amazon CodeWhisperer, and Tabnine.

One such new entrant, Devin AI, has been dubbed an “AI software engineer” by its maker, applied AI lab Cognition. According to Cognition, Devin can perform all these tasks unassisted: build a website from scratch and deploy it, find and fix bugs in codebases, and even train and fine-tune its own large language model.

Following its launch, open-source alternatives to Devin have cropped up, including Devika and OpenDevin. Meanwhile makers of established assistants have not been standing still. Researchers at Microsoft, GitHub Copilot’s developer, recently uploaded a paper to the arXiv preprint server introducing AutoDev, which uses autonomous AI agents to generate code and test cases, run tests and check the results, and fix bugs within the test cases.

“It’s exciting to see more versions of AI coding assistants with new capabilities,” says Ben Dechrai, a coder and developer advocate at software company Sonar. “They validate the need for generative AI tools in developers’ workflows.”

Dechrai adds that these coding copilots can help software engineers write code faster, allowing them to focus on more strategic and creative tasks. Another advantage of these programming tools is the ability to create a template for code, notes Saurabh Bagchi, a professor of electrical and computer engineering at Purdue University. Much as with prompt engineering, developers must provide these assistants with “the right kind of software requirements to produce a template, and then a software engineer can fill in the gaps,” he says.

These gaps include safety and reliability considerations. Software engineers must look out for security vulnerabilities in AI-generated code, as well as the types of corner cases that could cause it to crash.

“Developers still need to ensure rigorous quality standards are in place when analyzing and reviewing code written with generative AI, just as they would with code developed by a human,” says Dechrai. “AI coding assistants are good at suggesting code, reflecting on the code, and reasoning about its effectiveness, but even then it’s not 100 percent accurate.”

Dechrai cautions that autonomous coders are “still so new that developers are just learning which use cases will be most beneficial.” And they’ll need to be “ironed out in the real world to see how much they’re able to deliver on their promise,” says Bagchi.

AI Coders vs. the Humans
Doom-and-gloom predictions of replacing human software engineers are also bound to follow the emergence of these “AI software engineers,” but that won’t be happening anytime soon. Devin, for instance, resolved only 14 percent of a subset of GitHub issues from real-world code repositories. “There’s still a long way to go for it to become something I can rely on blindfolded,” says Bagchi.

He notes that these autonomous programming tools have another blind spot: the fact that software development happens in collaboration. Coding copilots try to do everything, and they might do it reasonably well. On the other hand, different software engineers have their own specialties—be it front end, back end, full stack, or data, to name a few—and they all work together to build a cohesive product.

“To develop intuitive systems, you need an iterative process with humans in the loop to provide feedback,” Bagchi says. “The fundamental human intuition, depth, and imagination has to be brought to bear.”

That’s why Bagchi believes these unassisted versions won’t be dominating the space that coding assistants hold—at least for now. “The models running underneath are similar in architecture, and as technology continues to evolve, both of them will get better,” he says. “But the Copilot or CodeWhisperer model seems most promising and is better suited to complex software development where humans work with the assistance of AI.”

Yet programmers “should start using these tools if they haven’t already, or they’ll risk getting left behind,” says Dechrai. “If you want to know if an AI coding assistant is truly beneficial, you have to use it yourself, get to know it, and see where it fails.”

Bagchi echoes the sentiment: “Try them out with the use cases you have and stress them with the kinds of software you’re creating.” But because unassisted coding copilots are a nascent technology, they are likely to improve rapidly. “So you have to track them,” he adds.

Moreover, software engineers will have to “consistently ensure code is secure, reliable, and maintainable throughout its life cycle,” Dechrai says. “It will always be up to the developer to properly understand the output and how it was generated.”

Source: https://spectrum.ieee.org/ai-code-generator


18
Robotics / RECOVERING 216 HOURS PER YEAR: TESLA & WAYMO
« on: April 15, 2024, 02:47:19 PM »
RECOVERING 216 HOURS PER YEAR: TESLA & WAYMO


Autonomous, electric, ride-sharing “car-as-a-service” (using robotaxis) has the potential to be 80% cheaper than individual car ownership. 

The average U.S. commuter currently spends a mind-numbing 52 minutes each day roundtrip, trapped in the confines of their vehicle—for average employees that’s equivalent to recovering 216 hours, or twenty-seven 8-hour days, during your year.

Freed from the task of driving, this time could be transformed into periods of relaxation, productivity, or even leisure. Ever thought of finishing a novel, practicing a new language, or perhaps indulging in some personal passions during your commute? 

The era of the robo-chauffeur promises just that.

In today’s blog, I’ll discuss the top two companies leading this transportation revolution... Tesla & Waymo.

Let’s dive in…

 
Tesla

Tesla has a secret plan is to deliver a global fleet of robotaxis—and I have every confidence Elon will make that happen. What’s his secret weapon? The release of Tesla’s newest iteration of Full Self-Driving or FSD 12, a radical departure from Tesla's previous versions.

Unlike prior systems, FSD 12 wasn't created from meticulously crafted lines of C++ code. Instead, it arose from the technology's ability to learn autonomously, imbibing billions of video frames to mimic human drivers.

A Tesla engineer, Dhaval Shroff, likened it to ChatGPT, stating, "It's like ChatGPT, but for cars."=

The essence here was replicating human learning processes through neural networks, processing massive data volumes to simulate human actions in intricate driving scenarios.

Historically, Tesla's Autopilot used a rules-based approach, a structure where specific situations triggered codified reactions. Lane markings, pedestrian movements, vehicles, signals, each elicited a programmed response. But FSD 12 turned this approach on its head. Instead of following rigid rules, Shroff's "neural network planner" emulated human behavior, learning not from pre-set conditions but from observing human drivers' actions in real-life scenarios.

Central to Tesla’s robotaxi objectives is a singular metric—"miles driven without human intervention.”

Elon's directive was clear: "I want the latest data on miles per intervention to be the starting slide at each of our meetings."

The goal?

Push the limits of the neural network until it surpassed human driving capabilities.

The team's discovery that optimal performance required training on at least 1 million video clips underscored Tesla's unique advantage in this race to full autonomy. And the way in which Tesla’s Autopilot learned is something that surprised even Elon. As he put it, “I mean the really wild thing about the end-to-end training is that it learns to read. It can read signs, but we never taught it to read … we never taught it what a car was or what a person was or a cyclist. It learnt what all those things are, what all the objects are on the road from video, just from watching videos. Just like humans.”

With nearly 2 million Tesla cars globally collecting data daily, the company was uniquely poised to train and constantly improve FSD 12.

As of April 2024, Tesla has rolled out v12.3.3 of FSD, now called FSD (Supervised), to over 5,000 cars. Under the driver’s supervision, FSD vastly improves the car’s autonomous capabilities—from making lane changes and navigating around other cars or objects, to making left and right turns and parallel parking. (As of the writing of this blog, Tesla is already beginning its initial rollout out of FSD (Supervised) v12.3.4.)

I personally love my Model S on FSD... 99.9% of time it gets me all the way to my destination, and it’s only tried to kill me once!

Waymo

Beginning life as Google's internal experiment in 2009, Waymo evolved under Alphabet into a dedicated venture aimed at bridging the vast divide between self-driving vehicles and revenue generating robotaxis.

In its commitment to reshaping the future, Waymo vehicles have traversed over 12 million miles since 2009, both in real-world environments and simulations.

The company's profound objective is to eradicate human errors that account for countless fatalities annually. Leveraging state-of-the-art camera and Lidar laser technology, Waymo's fleet is equipped to visualize the world in incredible detail, irrespective of the hour. This ability to navigate with precision owes much to real-time sensor data fused with intricately detailed custom maps. And with the computational prowess of server-grade GPUs and CPUs, Waymo's onboard systems can process this flood of data, ensuring that passengers experience a journey that's not only safe but efficiently plotted.

In August 2023, Waymo made history in San Francisco, as the company began allowing the public to pay for rides in its driverless cars.

This groundbreaking development saw Waymo's vehicles functioning as true robotaxis, offering a glimpse into a future where the traditional taxi experience is reimagined. With the Waymo One app, booking a ride is as intuitive as hailing an Uber, but what arrives is a gleaming white Jaguar from Waymo's 250-strong fleet. These vehicles, each valued at a staggering $200,000, are outfitted with an array of high-tech sensors and cameras, ensuring an unparalleled level of safety and efficiency.

Yet, despite their technological sophistication, rides remain affordable, with fares ranging from $18 to $21, on par with traditional ride-hailing services.

As Waymo continues to push the boundaries of autonomous transportation, the company's recent expansion into Los Angeles marks a significant milestone.

In March 2024, Waymo secured approval from the California Public Utilities Commission (CPUC) to extend its services to select areas of Los Angeles and the Bay Area. With an initial fleet of fewer than 50 cars, Waymo's operational territory encompasses approximately 63 square miles, stretching from the coastal charm of Santa Monica to the vibrant heart of downtown Los Angeles.

While the service currently excludes airport trips and freeway travel, the demand is palpable, with a waitlist of 50,000 eager Angelenos ready to experience the magic of autonomous rides.

For Waymo, the Los Angeles expansion represents more than just another market—it is a proving ground for the company's vision of the future. With a metropolitan population of 13 million, LA's intricate web of freeways, narrow streets, and unprotected left turns, coupled with its notorious traffic and distracted drivers, poses a formidable challenge.

Yet, the potential rewards are immense, with estimates suggesting that the LA market could generate up to $2 billion in revenue for the company.

Why This Matters

With the rise of autonomous vehicles, the landscape of the auto industry is poised for a seismic shift. 

Currently home to over a hundred brands, the next decade will witness a substantial consolidation in the automotive realm.

Two main forces will drive this: car usage rates and functionality.

Most cars today are utilized less than 5% of their potential, often gathering dust in driveways. With the advent of car-as-a-service, fewer vehicles will serve more people, disrupting the demand-supply chain. 

Additionally, in this new market, brand loyalty will wane. Consumers, attracted by efficiency and cost-effectiveness, will care less about the brand and more about the service.

Hence, a significant reduction in the number of automaker brands is anticipated, challenging giants in Detroit, Germany, and Japan.

Donald Shoup, an esteemed urban planning professor at UCLA, provides insight into another profound implication: the impact on real estate. With a staggering 2 billion parking spots in the U.S., Shoup points out the startling fact that “the area of parking per car in the United States is thus larger than the area of housing per human.”

Furthermore, he reveals the hidden costs of “free parking,” estimating U.S. expenditures between $102 billion to $374 billion—somewhere in the ballpark of the Medicare and national defense budgets. But what if these vast parking spaces become redundant? With autonomous vehicles on-demand, the demand for parking diminishes. Our cities could witness a commercial real estate boom, or perhaps, some of these spaces might metamorphose into thriving community centers or lush green parks.

The future of autonomous vehicles isn't merely about technological progression—it's about reshaping societies, economies, and urban landscapes.

But these aren’t the only vehicles transforming mobility. As we’ll see in the next few blogs, flying cars are finally on their way.


Source: https://www.diamandis.com/blog/abundance-47-dawn-of-the-robo-chauffeur


19
Generative AI / Why small language models are the next big thing in AI
« on: April 15, 2024, 02:41:16 PM »
Why small language models are the next big thing in AI


In the AI wars, where tech giants have been racing to build ever-larger language models, a surprising new trend is emerging: small is the new big. As progress in large language models (LLMs) shows some signs of plateauing, researchers and developers are increasingly turning their attention to small language models (SLMs). These compact, efficient and highly adaptable AI models are challenging the notion that bigger is always better, promising to change the way we approach AI development.

Are LLMs starting to plateau?

Recent performance comparisons published by Vellum and HuggingFace suggest that the performance gap between LLMs is quickly narrowing. This trend is particularly evident in specific tasks like multi-choice questions, reasoning and math problems, where the performance differences between the top models are minimal. For instance, in multi-choice questions, Claude 3 Opus, GPT-4 and Gemini Ultra all score above 83%, while in reasoning tasks, Claude 3 Opus, GPT-4, and Gemini 1.5 Pro exceed 92% accuracy.

Interestingly, even smaller models like Mixtral 8x7B and Llama 2 – 70B are showing promising results in certain areas, such as reasoning and multi-choice questions, where they outperform some of their larger counterparts. This suggests that the size of the model may not be the sole determining factor in performance and that other aspects like architecture, training data, and fine-tuning techniques could play a significant role.

The latest research papers announcing new LLMs all point in the same direction: “If you just look empirically, the last dozen or so articles that come out, they’re kind of all in the same general territory as GPT-4,” says Gary Marcus, the former head of Uber AI and author of “Rebooting AI,” a book about building trustworthy AI. Marcus spoke with VentureBeat on Thursday.

“Some of them are a little better than GPT-4, but there’s no quantum leap. I think everybody would say that GPT-4 is a quantum step ahead of GPT-3.5. There hasn’t been any [quantum leap] in over a year,” said Marcus.

As the performance gap continues to close and more models demonstrate competitive results, it raises the question of whether LLMs are indeed starting to plateau. If this trend persists, it could have significant implications for the future development and deployment of language models, potentially shifting the focus from simply increasing model size to exploring more efficient and specialized architectures.

Drawbacks of the LLM approach

The LLMs, while undeniably powerful, come with significant drawbacks. Firstly, training LLMs requires an enormous amount of data, requiring billions or even trillions of parameters. This makes the training process extremely resource-intensive, and the computational power and energy consumption required to train and run LLMs are staggering. This leads to high costs, making it difficult for smaller organizations or individuals to engage in core LLM development. At an MIT event last year, OpenAI CEO Sam Altman stated the cost of training GPT-4 was at least $100M.

The complexity of tools and techniques required to work with LLMs also presents a steep learning curve for developers, further limiting accessibility. There is a long cycle time for developers, from training to building and deploying models, which slows down development and experimentation. A recent paper from the University of Cambridge shows companies can spend 90 days or longer deploying a single machine learning (ML) model. 

Another benefit of SLMs is their potential for enhanced privacy and security. With a smaller codebase and simpler architecture, SLMs are easier to audit and less likely to have unintended vulnerabilities. This makes them attractive for applications that handle sensitive data, such as in healthcare or finance, where data breaches could have severe consequences. Additionally, the reduced computational requirements of SLMs make them more feasible to run locally on devices or on-premises servers, rather than relying on cloud infrastructure. This local processing can further improve data security and reduce the risk of exposure during data transfer.

SLMs are also less prone to undetected hallucinations within their specific domain compared to LLMs. SLMs are typically trained on a narrower and more targeted dataset that is specific to their intended domain or application, which helps the model learn the patterns, vocabulary and information that are most relevant to its task. This focus reduces the likelihood of generating irrelevant, unexpected or inconsistent outputs. With fewer parameters and a more streamlined architecture, SLMs are less prone to capturing and amplifying noise or errors in the training data.

Clem Delangue, CEO of the AI startup HuggingFace, suggested that up to 99% of use cases could be addressed using SLMs, and predicted 2024 will be the year of the SLM. HuggingFace, whose platform enables developers to build, train and deploy machine learning models, announced a strategic partnership with Google earlier this year. The companies have subsequently integrated HuggingFace into Google’s Vertex AI, allowing developers to quickly deploy thousands of models through the Google Vertex Model Garden.

After initially forfeiting their advantage in LLMs to OpenAI, Google is aggressively pursuing the SLM opportunity. Back in February, Google introduced Gemma, a new series of small language models designed to be more efficient and user-friendly. Like other SLMs, Gemma models can run on various everyday devices, like smartphones, tablets or laptops, without needing special hardware or extensive optimization.

Since the release of Gemma, the trained models have had more than 400,000 downloads last month on HuggingFace, and already a few exciting projects are emerging. For example, Cerule is a powerful image and language model that combines Gemma 2B with Google’s SigLIP, trained on a massive dataset of images and text. Cerule leverages highly efficient data selection techniques, which suggests it can achieve high performance without requiring an extensive amount of data or computation. This means Cerule might be well-suited for emerging edge computing use cases.

Another example is CodeGemma, a specialized version of Gemma focused on coding and mathematical reasoning.  CodeGemma offers three different models tailored for various coding-related activities, making advanced coding tools more accessible and efficient for developers.

The transformative potential of small language models

As the AI community continues to explore the potential of small language models, the advantages of faster development cycles, improved efficiency, and the ability to tailor models to specific needs become increasingly apparent. SLMs are poised to democratize AI access and drive innovation across industries by enabling cost-effective and targeted solutions. The deployment of SLMs at the edge opens up new possibilities for real-time, personalized, and secure applications in various sectors, such as finance, entertainment, automotive systems, education, e-commerce and healthcare.

By processing data locally and reducing reliance on cloud infrastructure, edge computing with SLMs enables faster response times, improved data privacy, and enhanced user experiences. This decentralized approach to AI has the potential to transform the way businesses and consumers interact with technology, creating more personalized and intuitive experiences in the real world. As LLMs face challenges related to computational resources and potentially hit performance plateaus, the rise of SLMs promises to keep the AI ecosystem evolving at an impressive pace.

Source: https://venturebeat.com/ai/why-small-language-models-are-the-next-big-thing-in-ai/





20
Robotics / THE BIRTH OF ROBOTAXIS (CAR-AS-A-SERVICE)
« on: April 11, 2024, 09:54:42 PM »
THE BIRTH OF ROBOTAXIS (CAR-AS-A-SERVICE)


How would your life improve if you never had to drive again? If traveling across town to work or your friend’s home was cheap and fully autonomous, enabled by a robotic chauffeur?

How much time would you save if you weren’t the one behind the wheel? What would you do with those extra hours?

Over the next few blogs in this Age of Abundance series, we’ll discuss an additional category of advanced robotics, namely autonomous vehicles, flying cars or eVTOLs (electric Vertical Take-off or Landing), and delivery robots helping to get people and goods from one point to another.

Fully autonomous vehicles from Tesla and Waymo (to name a few) are on the path to enable “car-as-a-service” fleets (or robotaxis) operating on-demand, Uber-like services.

The cost of ground transportation is slated to decrease between 2x to 4x as a result. Sometime in the near future, your kids or elderly parents will never drive.

A significant percentage of parking garages, driveways, and parking structures will eventually be transformed into alternative usable space. Autonomous cars will take all shapes and sizes and serve as functional “third spaces” used for entertainment, sleeping, or meeting rooms as drive time becomes work or play time.

Meanwhile, aerial ridesharing, eVTOLs, and flying cars will also become fully operational in most major metropolitan cities this next decade.

Where you live and work will begin to transform as these systems shrink travel time and distance. Previously difficult to reach geographies (islands, rural areas, mountain tops) will become accessible.

Individuals seeking the solitude of the country will also have access to the shopping, food, and entertainment of metropolitan city centers, connected through eVTOL technology.

In today’s blog, we’ll go back in time to the early 2000s, when a series of Grand Challenges laid the foundation for today’s autonomous vehicle industry.

Source: https://www.diamandis.com/blog/abundance-46-birth-of-robotaxis


21
Solar / Solar Energy Landscape of Bangladesh
« on: April 06, 2024, 03:43:21 PM »
Solar Energy Landscape of Bangladesh


Bangladesh is currently experiencing a crisis as a result of both internal and international issues. Fossil fuels like natural gas and oil are used to create around 85% of the country’s power, with natural gas serving as the main fuel source. OPEC+ oil production cutbacks, the European Union’s embargo on Russian crude oil, and Russia’s energy war have all contributed to an exponential spike in oil and gas prices, which has led to unaffordable energy import costs and soaring inflation.

Bangladesh was compelled to cease buying gas and shut down many diesel-powered power facilities as a result. The lack of renewable energy sources in the country and measures like capacity payments have also made the situation worse. However, regardless of the low share of renewable energy in the country’s power mix, there lies immense potential for solar power electricity generation.

The country has begun focusing on the integration of renewable energy following the Paris Agreement. Numerous infrastructural projects are being developed that include mega projects and industrial zones. These industrial zones and parks are planned to be eco-friendly with the inclusion of solar energy and wastewater management. Additionally, organizations will also receive government incentives for using clean energy sources such as biomass, wind, and solar.

Power Sector Overview of Bangladesh

As of 2022, the country’s total power generation capacity (on-grid and captive sources) is 25.5 GW, and it has grown significantly over the past 5 years, and this has been a major cause of the increase in GDP.

The country has also achieved a 98% electrification rate in the year 2021, bringing the majority of the population under electrification. The on-grid maximum energy generated was 14.78 GW in FY 2021-22, while the on-grid generation capacity was 22.07 GW.



Natural gas has remained the primary and cheapest source of energy over the last decade. However, a reduction in the number of explorations and growing demand has depleted gas reserves. This has increased dependency on imported LNG and Heavy Fuel Oil (HFO).

The recent Russia-Ukraine conflict has increased the price of LNG by nearly 165%. The current fuel mix of Bangladesh’s power plants heavily depends on natural gas, oil,  coal, and diesel (jointly >80%). Because of the current energy prices in combination with the expected depletion of natural gas resources within 10 years, the GoB plans to reduce dependence on domestic natural gas. This is done by increasing the use of imported liquified natural gas (LNG), importing more electricity from neighboring countries, and expanding the use of renewable resources, especially solar power.

Country’s Active Focus Towards Renewable Energy

Bangladesh has pledged to the Climate Vulnerable Forum to generate 40% of electricity from renewable sources by 2041. This would result in a 16 GW RE capacity (target of 30%) in 2031 and a 40 GW RE capacity (target of 40%) in 2041. At present, 3.7% of the total energy mix is contributed by renewable sources, of which approximately 75% (or 2.8% of the total energy mix) is contributed by solar energy.

Other renewable energy sources, such as hydro and wind, have shown limited growth due to geographical limitations. As a result, the prospects of wind and hydropower are relatively low. In contrast, the potential for photovoltaic (PV) is much higher and consistent throughout the entire country. 

The Government of Bangladesh had envisioned that renewable energy would contribute to 10% of the total amount of energy produced by 2020. Yet, the present amount is only 3.7%. Hence, the 40% target has been reinstated till 2041. However, as per industry experts, the aspirations seem to be optimistic.

Nevertheless, the state prioritizes utilizing power generated from renewable over non-renewable sources. According to government officials, multiple solar projects with a combined capacity of over 3 GW are scheduled for the upcoming years.

High Prospects for Solar Energy in the Rooftop Solar Segment

The government has planned to prioritize solar energy in the long run. Difficulties in attaining land for solar parks and solar grid facilities have shifted the focus towards rooftop systems with net metering systems and DRE solutions.

Floating solar is given priority considering the enormous amount of water available. However, at present, floating solar is still in a nascent state as enough research has not been done on its prospects.

According to the SREDA, the split between off-grid and on-grid solar energy solutions is nearly 50% – 50%. The recent growth in off-grid solutions can be attributed to solar home systems, solar irrigation, and rooftop solar systems without net metering.

The overall renewable energy landscape is divided between small-scale projects and large-scale projects. But most capacity resides in large-scale solar projects, including solar-powered rooftops, irrigation, mini-grids, microgrids, nano-grids, and solar charging stations. Most small-scale renewable energy projects consist of solar-powered home systems and streetlights.

At present, 3 kinds of solar projects are taking place in the country: captive solar rooftops, solar IPPs, and solar home systems. Out of these, captive solar rooftops have the highest prospect among the rest as industrial players are reducing their reliance on diesel and gas due to the instability of prices.

Solar IPPs are being implemented as well. However, the scarcity of a prominent-sized landmass is hindering the growth of this avenue. Lastly, solar home systems experienced significant growth in the last 5 years due to IDCOL’s SHS program. However, with the current electrification rate being 98%, the rural population got access to electricity, and this caused slow growth in the sector.

The current market is dominated by Chinese-manufactured solar equipment. Local EPC contractors act as official dealers of the equipment and provide end-to-end turnkey project execution that includes both CAPEX and OPEX models. Demand for European products persists. However, unsatisfactory after-sales service has hampered the demand for the products.

Persisting Bottlenecks in the Solar Sector

The country’s aspirational goal of achieving the 30% renewable energy target is optimistic, given the current status quo. Additionally, the renewable energy policy was released in 2008 and is considered to be dated.

Even though the net metering policy was initiated in 2018, it only focused on the ability to transfer excess energy to the grid in return for a credit on the bill. The lack of specific policies for different projects has led to lower sector-wise adoption.

Strong mandates have to be set with proper incentives in order to increase the usage of renewable energy sources. In 2010, the government had set a mandate for all residential and commercial buildings to install solar panels in order to attain electricity connection. However, adopters have installed low-quality panels due to low awareness of their benefits. As a result, the majority of buildings now have unusable solar panels that are not properly inspected by the governing bodies.

The current grid connectivity does not allow DRE solutions (irrigation, water purifiers, etc.) to entail under the net-metering guideline. Additionally, multifold decades-old grid infrastructure does not properly support the variable renewable energy. Along with it, the last mile population does not have grid access due to geographical positioning, for which they rely on captive power plants that cannot benefit from the net metering policy.

On the other hand, domestic manufacturers have failed to sustain themselves in the market due to lower economies of scale and high demand for international products. The government has supported the domestic players by increasing taxes on imported panels. However, the tax structure remained the same even after domestic players left the market, causing increased market prices of solar panels.

Investing in solar solutions requires heavy financing that the majority of the banks fail to provide even after the central bank’s mandate to disburse 5% of their total loans as “green loans”.

Only Infrastructure Development Co. Ltd., a government-owned NBFI, has sufficient resources to understand this artificial income stream and to analyze the feasibility of the project before approving the loan. However, most organizations lack this capacity. As a result, it is difficult for companies to attain these loans.

Opportunities to Explore

As the growing RMG sector is following compliant criteria to capture more market share, demand for solar rooftops has been growing. Most of the apparel industry players use captive power plants to generate electricity. However, the current rise in fuel prices has opted them to shift towards renewable solutions. This growing demand will help Dutch players to capitalize on their advanced technology.

Furthermore, solar energy could be integrated into cold chain storage of perishable products (eg. agri-food, pharmaceuticals) and water desalination. Dutch R&D of high-tech solar panels with high productivity/yield can also be integrated into greenhouses to foster sustainable protected cultivation in Bangladesh.

Solar can also be integrated into the aquaculture sector, by fostering the development of large solar-powered fish farms and the development of floating solar parks combined with the sustainable growth of fish and other water species.

Since solar energy solutions are expensive, there is room for the OPEX model to grow and reduce dependency on CAPEX models.

Removing the financial burden on implementers will help them easily install solar energy. Awareness among smaller and medium-sized players regarding the potential business case and benefits of solar installation can be explored. This will reduce the dependency on low-quality PV panels, inverters, and transformers with high-quality equipment, leading to increased yields.

Lastly, the technical knowledge of financial institutions can be improved to allow more companies to have access to finance. The current refinancing scheme should increase the minimum loan amount of BDT 100 million for a net-metered rooftop system, as most of the industrial players are in need of more funds.

Additionally, the 5% ‘green loans’ target set by the central bank should be stricken through the penalization of banks for not meeting the set target. 

Source: https://www.lightcastlebd.com/insights/2023/03/solar-energy-landscape-of-bangladesh/





22
Our Skilled and Leadership Competitions are Cutting Edge

Overview

The competitions of the SkillsUSA Championships are created and judged by industry to ensure that students are learning the real-world skills employers demand from entry-level professionals. Learn more about our competitive events below. These competitions represent some of the most highly skilled, in-demand skilled trade areas in the nation.


For more details, please visit the following link: https://www.skillsusa.org/competitions/skillsusa-championships/categories-and-descriptions/

Source: https://www.skillsusa.org/competitions/skillsusa-championships/categories-and-descriptions/



23
Horticultural Value Chain – Overcoming Long-Standing Challenges


Bangladesh has long set its sights on becoming a middle income economy by 2026 and has determined to achieve the targets of Vision 2041, which includes aspects like increasing export earnings to $300 billion, increasing life expectancy to 80 years, and bringing down the poverty rate to less than 3%.

Studies show that high-value horticultural crops including fruits, vegetables, aromatic plants, herbs, and flowers, have been playing a key role in agricultural development and economic progress in developing countries. [1] They not only reduce malnutrition by contributing a balanced, diversified, and nutrition-rich diet but also decrease poverty through increased income and women empowerment.

On the other hand, these high-value crops can be a significant addition to our export basket as the global horticulture market is expected to reach $40.24 Billion by 2026 at a CAGR of 10.2%. [2]

In 2021-22, crops and horticulture contributed to 5.64% of the total GDP, which amounted to 20.487 billion USD. [3] Currently, 7% of total crop production in Bangladesh comes from horticulture, while it utilizes only 4% of the total farming area. [4]

However, agricultural land is decreasing due to the rise in sea level, and by 2050, Bangladesh is projected to lose 11% of its total land, displacing 18 million people. [5] Besides, as per the World Bank, Bangladesh will lose 18% of its cropland on its southern side and could lose a third of its agricultural GDP. [6]

Along with calling for mitigating steps to abate the effects of climate change, there’s a need for developing higher-yielding crops to best utilize the remaining land and to ensure food safety for the increasing population.

In this situation, improving the horticultural value chain management as a whole, starting from the input suppliers to the output traders, can go a long way in alleviating the stress resulting from the irregularities existing in the value chain of this highly prospective sector.

Quick Overview of the Horticulture Industry of Bangladesh
Horticulture is that branch of agriculture science that refers to the commercial plantation of flowers, fruits, and crops for the purpose of profit. The overall division of this branch is demonstrated in the figure below:


Figure: Breakdown of Horticulture Segment of Agriculture Science

Bangladesh produced 1.97 crore tons of vegetables on 9.35 lakh hectares of land as of FY 2020-21, and the production has increased by seven folds in the last 12 years causing Bangladesh to be the third-largest producer of vegetables in the world. Bangladesh currently grows 100 species of vegetables. [7]

Again, the floriculture sector of Bangladesh is also booming which grows a total of 50 variants of flowers and, as per BBS, Bangladesh produced a total of 32,120 tons of flowers on 3,930 acres of land, and the export earnings stood at $80,000 from this sector in FY 2022-23. [8].

Lastly, at present Bangladesh lists among the top 10 countries of the world for producing seasonal fruits, with a total annual production of 1.22 crore fruits of 72 different varieties.[9]. For export, Horticulture products are mainly destined for the markets of the Middle East, United Kingdom, and Italy, targeting the large Bangladeshi Diaspora.

The Challenges Persisting in the Horticultural Value Chain


The value chain in horticulture has three key groups of actors: input suppliers, primary producers, and produce traders.

1. Input Suppliers

The main inputs in horticulture are seeds, saplings, fertilizers, insecticides, and pesticides. When it comes to seeds, Lal Teer is the largest local vegetable seed producer and distributor company. Besides this, there are at least 20 other companies active in the industry and also many smaller unorganized players. Overall, in Bangladesh, the seed distribution network comprises over 17,000 dealers, 160,000 retailers, and 4,500 mobile vendors. [4]

Fertilizers are mainly supplied by BADC, a government agency, while a huge portion is imported. Crop production products are supplied by big companies like – Syngenta, Bayer Crop Science, Partex Agro, and Petrochem. At the local level, they share the same distribution channels as seed manufacturers. [4]

Challenges:

* Difficult to Determine the Quantity of Seeds Produced: As per the Horticulture Study of Bangladesh, the lion’s share (55%) of the seeds produced and distributed is controlled by the informal market. So it is often not possible to get accurate data on the supply and demand balance as seeds are still collected from farms or small suppliers through informal channels

* The Areas with No Seed Production often Lack the Necessary Seed Supplies: The seeds produced from farming are sold to the collectors (middlemen) who then sell them to the market. These collectors often sell the seeds only to the region of origin for their own convenience and also fail to supply owing to weak transport networks during the rainy season and natural disasters and thus failing to cater to the regional demands of seeds in the areas with no seed production.

* Large Counterfeit Seed Market: A World Bank report highlights the lack of a conducive, regulatory framework for seed development and sufficient production as a key reason for the shortage of quality seeds. Besides, other studies show that a lack of regular and effective market inspections has sustained a large counterfeit seed market in the country

* 80% of the Fertilizer Supplied is Imported: As per Bangladesh Fertilizer Association (BFA) and USDA 2022, the total annual demand for chemical fertilizers in Bangladesh is 6 million metric tons of which 80% is imported. This huge import dependency makes the product extremely vulnerable to global market conditions

* Lack of Proper Training on the Efficient Use of Fertilizer: Lack of proper crop-specific or soil-specific fertilizer use analysis and lack of proper soil fertility analysis, results in inefficient use of fertilizer despite Bangladesh having one of the highest concentrations of fertilizer use in crop production

2. Primary Producers

As per the National Agricultural Census of 2019, 16.5 million households contribute to farming in Bangladesh. Out of the rice and vegetables that they grow in rotation, less than 20% is consumed by the farming households themselves. [4] As per a report by USAID, vegetable farmers grow on a very small scale, 60% of them cultivate on land measuring one acre or less, while commercial vegetable growers comprise only 1%.


Figure: Consumption of Primary Produce In Bangladesh

Challenges:

Unmechanized Cultivation Practices: Traditional cultivation practices are still prevalent in this field. Lack of mechanization and proper technical farming knowledge deprives the farmers of higher returns on their investments and higher productivity and efficiency.

Different Regional Farming Areas of Bangladesh are Impacted by Climate Change: While the farmers of the southern belt suffer from salinity intrusion, the farmers of the northwest region are affected by drought and the impact of floods covers all the regions of the country. Besides, the shortening of the winter season is a new threat to these horticulture farmers.

Inefficient Production Planning Leading to Lower Price of the Produce: Falling for “pig cycle” dynamics, planning production quantity based on the higher price of last season increases the overall production in the following season and hence brings down the price, and being affected by several natural calamities, it gets harder for the farmer to efficiently plan their production quantity

Farmers have Little Means to Exercise their Power in Price Negotiations: Farmers are not organized in any cooperative and hence within this highly price-volatile market they have little to no say

Other Challenges: The decrease of farmable land, growing population, underdeveloped rural economy, frequent flooding and other disasters related to climate change, and the promise of income opportunities offered by urban areas are resulting in large numbers of farmers migrating to the cities every year. [10][11]


Figure: Simplified Version of the Horticultural Value Chain

3. Traders

There are several intermediaries in the chain named farias, beparis, and arothdars, which thus makes the chain from the farmers to the end consumers a lengthy one.

Small-scale farmers sell their produce to an aggregator who takes them to the market yard, where marketing activities like assembling, grading, storage, sale, and purchase take place.

Large-scale wholesalers purchase the produce, selling them to smaller ones. Finally, the crops go through retailers to the final consumers. The intermediaries present in each stage of the supply chain play an important role in linking two parties to each other. A simplified version of the supply chain is shown in the figure below:

Challenges:

Long Supply Channels Depriving Farmers of Fair Price: Long supply channels present in the country are the main reason farmers complain of not getting a fair price for their produce. Farmers on average get less than 20% of the share of the consumer price of horticultural products, whereas 45% of the price is jointly shared by the traders (farias & arothdars)

Huge Post-Harvest Production Loss: Inadequate storage facilities and cold storages in both production areas and wholesale markets, poor market infrastructure, and poor post-harvest treatment and transportation result in huge post-harvest production loss, which as per a study of ADB, if decreased by 75% then would represent an annual savings of USD 1.8 billion

Only 1% of the Horticulture Produce is Sent for Processing: This creates a huge untapped market potential and deprives farmers and traders of a better price and value for the produce. Horticulture processing takes up a very small portion of the food-producing sector which is worth $8.3 billion annually

Dhaka Centric Trading Market: Besides, the lack of finance and agriculture insurance, Dhaka is still the main wholesale market for horticultural produce, causing the trading being done in a highly congested and unhygienic market place which further brings down the quality and price of the horticultural produce

Case Studies on the Bottlenecks of the Horticulture Sector of Bangladesh

Among various horticultural crops, vegetables are one of the most highly consumed. [9] Annually, a total of 6.5 million tons of 150 varieties of vegetables are produced. Yet, USD 203 million worth of vegetables were imported in 2019.

Surprisingly, some of the highest levels of imports amount to crops we are entirely capable of producing ourselves geographically. In the Year 20-21, 28.066 billion BDT (265. 08 million USD) worth of onion and garlic [12] were imported.

Here’s a look at the challenges present in the value chains of Bangladesh’s most consumed crops.

Challenges in the Value Chain of Onions

One of the main challenges in onion farming is the yield gap, the difference between yield potential and actual yield, which is present due to managerial incompetence leading to yield losses. In 2022, Bangladesh imported 0.67 million tonnes of onion, which is an increase of 0.11 million tonnes compared to the previous year.

Even though the production in the 2021-22 fiscal year was a record high of 3.504 million tonnes, [13] this rise in import can be owed to the disruption of the supply chain due to flooding [13] as well as post-harvest losses caused due to lack of cold storage facilities. [14]

In contrast, India harvested 26.64 million tons of onion in the fiscal year 2021-22 and is estimated to increase to 31.12 million tons in 2022-23 as the acreage increased from 1.62 million hectares to 1.91 million hectares in just a year. [15] Their post-harvest loss management is in much better shape with available cold storage. To reduce post-harvest losses further to 10-12%, they plan to do gamma-ray irradiation before sending the harvested onions to cold storage. [16]

Challenges in the Value Chain of Tomatoes

Tomato production all year round is increasing and farmers have accepted hybrid seeds sourced locally. In Bangladesh, tomato is produced with traditional methods on open land as well as in a controlled setting of greenhouses and polytunnels. Even with such advancements, the post-harvest loss is as high as 40% in tomato production. [4]

Tomatoes happen to be perishable in nature and it’s challenging to keep them fresh. External damages, harvesting at incorrect maturity stage, disease and insect infestation, and lack of proper storage are factors that mainly contribute to the losses. There’s a demand for tomatoes in the agro-processing industry that isn’t met locally due to such high losses.

Way Forward in Overcoming the Long-Standing Challenges


In order to remedy some of the long-standing challenges within the horticultural value chain in Bangladesh, a number of initiatives, avenues, and opportunities can be pursued.

A Move Towards Ensuring Quality Outputs by the Supermarket Retailers

An increasing number of super shops and online grocery companies are running parallel supply chains that cut through some of the intermediaries to offer traceable, quality produce to high-end customers.

The supermarkets are expected to grow bigger in ensuring fresh produce and fresh products as the country transitions towards urbanization. This drive will move upward improvement where the suppliers will be encouraged to ensure better production, as well as harvesting and post-harvesting techniques.

Higher investment in modernized refrigerated transport, temperature-controlled warehouses, and distribution centres are expected by supermarket retailers.

Online Grocery Startups are Improving the Value Chain

Companies like Chaldal have built their own network [17] of farmers and small-scale retailers, connecting the two. This in effect ensures that farmers get a much fairer price and a better lifestyle.

The retailer benefits from traceability as they can return produce that doesn’t meet quality standards. Their long-term collaboration with farmers and small-scale retailers enables online grocery startups to bulk supply vegetables and earn most of their revenue. Their online marketplace cuts the cycle even shorter than their B2B model as they use their own network of farmers and directly cater to consumers through the same network. Besides, other online grocery platforms are FoodPanda, HungryNaki, Pathao, Daraz Mart, SodaiHut, etc.


Figure: Supply Chain for Online Grocery Stores and Supermarket Retailers

Other Promising Developments in Improving the Value Chain

There’s a long way Bangladesh needs to go in terms of the horticultural value chain. But some of the recent developments show promising changes that can result in improvement.

First GAP Certificate

In January of 2023, AR Malik Farms became the first farm in Bangladesh to receive good agricultural practices (GAP) certification. [18]

As the certificate reassures that the food produced meets globally accepted standards of safety and quality, this improves the cultivator’s reputation and opens up previously untapped marketplaces that question food safety seriously. This can be a stepping stone in acquiring the agro-products market in Europe as sanitation has always been the primary issue in exporting there. For that to happen, more farms need to follow the example of Malik Farms.

For GAP certification, working with an experienced consultancy firm like SGS is a great way to improve quality management and regulate food safety in every stage of production to marketing. The company delivers GLOBAL GAP certification in over 30 countries including Bangladesh.

New Research Centers

Inadequate research and innovation have also been a barrier to improving yield and developing varieties to combat climate change.

The government took the initiative of setting up the Bangabandhu-Pierre Elliott Trudeau Agricultural Technology Centre at BRRI in partnership with the Global Institute for Food Security at the University of Saskatchewan in Canada with the view to cooperation in research, ensuring sustainable food security, training, and development partnership programs. [19]

Increased emphasis on providing research stipends and providing agriculture-based education at higher levels is also aimed toward technological advancement in agriculture.

Use of AI in Agriculture

The use of AI in aquaculture and dairy farming is an inspiring example of innovation. Akbar Hossain is an agricultural entrepreneur who brought the in-pond raceway system (IPRS) to Bangladesh. IPRS allows more fish to be farmed in less water by ensuring optimal water chemistry, especially adequate oxygen supply. [20]

ACI Agribusiness introduced an AI-based app called Rupali. It sends automated suggestions to fish culturists based on the scanning of different patterns with a view to maintaining water quality.

There have been some small changes in the horticulture sector too. An AI-based company, iPage is helping farmers conduct instant soil tests to improve their farming conditions. The company also focuses on aiding farmers with information about correct farming practices and ensuring proper value for products.

While still working on making something as basic as soil testing accessible, IoT, Probe sensors, data analysis, and automated greenhouse may seem like a thing of a faraway future for Bangladesh, but the government is trying to make it happen with the vision of 4AR or Agricultural Revolution 4.0. [21]

Conclusion

While Bangladesh paves its way to achieving its economic and developmental targets, such as graduating LDC status by 2026, horticulture has already been considered an important stepping stone in this path. Hence, various policies regarding process modernization and product diversification for this sector have been undertaken.

However, not every initiative to improve the sector is going smoothly. There are still various challenges lingering in different parts of the supply chain, but with enhanced public-private partnerships and increasing interest of foreign investors in the horticultural and agricultural sector of Bangladesh, there are hopes to see an efficient resolution of the current dysfunctionalities in this sector.

As India has already shown to benefit from investing in cold storage, the leap could have been taken quicker in Bangladesh as well. Necessary steps should be taken to develop a proper window for sustained collaboration between the public and private sector players in this value chain of high potential to reap valuable benefits in terms of employment generation, entrepreneurship growth, per capita production increase, and protecting our valuable foreign currency from vegetable imports.

Source: https://www.lightcastlebd.com/insights/2023/05/bangladesh-horticultural-value/


24
Analyzing the Growth Opportunities and Systemic Bottlenecks in Bangladesh Aquaculture


Aquaculture is defined by the UN’s Food and Agriculture Organization (FAO) as the farming of aquatic organisms including fish, molluscs, crustaceans, and aquatic plants. Farming implies some sort of intervention in the rearing process to enhance production, such as regular stocking, feeding, protection from predators, etc. Farming also implies individual or corporate ownership of the stock being cultivated, the planning, development, and operation of aquaculture systems, sites, facilities, practices, production, and transport.

Aquaculture, which has existed for thousands of years, began significantly contributing to global food supplies and rural economies approximately three decades ago. In 1974, aquaculture accounted for only 7% of fish for human consumption, but by 1994, this share rose to 26%, and by 2020, it reached 46%.

Over the past 50 years, per capita consumption of aquatic foods has more than doubled, averaging around 20.2 kg globally in 2020. Consequently, global production soared to 214 million tonnes by 2020, with aquatic foods supplying approximately 17% of the world’s animal protein intake, exceeding 50% in some Asian and African countries.

Changing Global Trends in Aquaculture

In recent times, there has been a notable shift in aquaculture towards more semi-intensive and intensive methods of farming, marking a significant change in the industry’s approach. This shift is driven by the goals of achieving greater profitability and productivity.

The Food and Agriculture Organization (FAO) notes that this change is necessitated by the growing global demand for seafood, coupled with the need for better use of resources. The transition from Extensive to Semi-intensive farming involves controlled pond environments, while intensive farming uses sophisticated technologies like recirculating aquaculture systems (RAS).




25
Micocredentials – preparing school students for life after graduation


Microcredential courses can help school students build professional skills and enhance future employability.

Microcredential programs are a way that secondary schools can help their students build key skills and knowledge to thrive in study or work after they graduate. These short courses are typically on offer from, or developed in partnership with, external institutions such as universities.

‘Microcredentials are a quick, easy and affordable way to upskill and provide professional and “soft skill” development for young people entering the workforce or embarking on further education,’ Brendan Begley, Deputy Principal at Queensland’s Cairns State High School (CSHS) tells Teacher.

‘They also provide an opportunity for a “taster” into different disciplines before committing to longer term study options, and in some instances may offer a credit pathway to further study.’

It’s for those reasons that CSHS decided to pilot its own microcredential program in 2023, in partnership with CQUniversity.

‘[We] were interested in providing opportunities for our current year 12 cohort to gain additional employment/workplace/study skills to take with them as part of their portfolio on graduation,’ Begley explains.

Working in collaboration with staff from the Centre for Professional Development at CQUniversity, 5 microcredentials developed by CQUniversity were selected for the year 12 cohort to complete. The microcredentials were chosen by a team of CSHS staff – including administration staff, guidance officers, and year coordinators – based on the students’ identified needs. These needs included building confidence in academic writing (in preparation for future study) and developing work-ready skills in students that had no prior work experience.

As part of discussions that arose, it was decided that these courses would also be extended to the recently graduated class of 2022, while a modified program would be offered to the year 11 cohort – one that was more focused on skills that would benefit them while still at school, such as public speaking, study habits and note taking.

All students in these cohorts were automatically enrolled (around 750 in total) while Connect Teachers (at CSHS, Connect Teachers help foster a sense of belonging, connecting students and parents with services, activities and more) were enrolled as ‘non-editing teachers’, allowing them to monitor progress and provide support to students who needed it.

Of the students that took up one or more of the options on offer, most successfully completed the microcredential courses selected, and feedback on the program from these students was positive. However, Begley says not all students enrolled actually took up the opportunity ­– something the CSHS is keen to improve in future.

‘Our goal was for 75% of students to complete 2-3 micro credentials from the 5 options on offer,’ he says. This goal wasn’t met, in part due to certain barriers, like the need to access particular IT resources not available for use in the Department of Education (meaning students would need to work independently at home).

‘We would have expected greater completion if students had been supervised and supported to complete these qualifications whilst at school,’ Begley reflects.

While the team at CSHS see a positive future and plenty of potential in microcredential programs at the school, funding for the program came through subject fees from parents and carers and cost-of-living pressures mean the the program has been paused for 2024. The plus, Begley says, is that this allows time for some reflection, with the program planned to return in 2025, even better than before.

Source: https://www.teachermagazine.com/au_en/articles/micocredentials-preparing-school-students-for-life-after-graduation


26
How to avoid the headaches of AI skills development

Most executives don't understand their team's AI skills. But some pioneering companies are taking action.



Andriy Onufriyenko/Getty Images

Adopting artificial intelligence (AI) to assist with tasks in business and technical functions looks good on quarterly reports for shareholders. But throwing technology into an organization doesn't deliver overnight miracles.

The big challenge with AI is that many business and IT leaders aren't sure whether their organizations are ready to handle it productively, according to a recent survey of 1,200 IT executives and professionals by Pluralsight.

While 81% of IT professionals are confident they can integrate AI into their roles, only 12% have significant experience working with the technology. To complicate matters further, 90% of executives don't completely understand their team's AI skills and proficiency.

"Even as organizations accelerate AI adoption, the majority don't understand what, if any, AI skills their employees possess or have an upskilling strategy to develop them," the study's authors point out. "The AI skills gap doesn't only apply to advanced technical skills, either. To make the most of AI, organizations need an accurate way to benchmark AI skills across their organization and use their insights to create a plan for skill development. This should include basic AI literacy as well as hands-on experiences where employees can apply what they learn, experiment, and make mistakes in a safe environment."

The AI skills gap impedes long-term success, the survey shows. Almost all executives and IT professionals (94%) believe AI initiatives will fail without staff who can use AI tools effectively.

Executives and IT professionals agree that investing in talent, training, and culture is the top step organizations should take to prepare for emerging AI tools. Yet only 40% of organizations offer formal structured AI training.

Some leading organizations recognize the potential of AI and are taking proactive measures to address the challenge of preparing their workforces for AI -- even employing AI itself to boost AI skills.

For example, Johnson & Johnson has launched a concerted effort to prepare employees for an AI-driven economy.

"We hire learners," Johnson & Johnson CIO Jim Swanson said. "Everyone in our organization has an objective that focuses on how they'll grow and develop their skills in 2024. Our global, AI-powered learning platform, J&J Learn, offers courses like a six-week digital immersion program to build capabilities in product management, design thinking, and artificial intelligence."

Core technology skills essential in today's AI era include software development, cloud engineering, data management, and network operations, Swanson said: "Just consider how foundational elements like data and elastic compute fuel the AI models that are currently in the spotlight."

However, AI isn't just important for technology professionals. Swanson said everyone across the organization should play a role in digital growth. "Leaders should take an active part in equipping their employees with critical future-ready skills, like how to responsibly apply generative AI to improve productivity, how to leverage intelligent automation to speed operations, or how to simulate steps in a supply chain with digital twins or augmented reality," he added.

J&J also incentivizes learning "through a month-long challenge where associates hone their technical and leadership skills, with points earned translating into donations for students in need globally," Swanson said. "We believe that training is critical, but it is through experience that this upskilling takes its full dimension. We pair these digital upskilling courses with growth gigs and mentorships, providing the opportunity to reinforce learning through experience and exposure." 

While AI is all about leading-edge technology, Swanson said using tools is only part of the story. "Even as we reimagine how we work through technology, we will always need people in the center to guide our innovation," he said. "The business of technology is distinctly human, and we need to foster soft skills like customer-centricity, people leadership, and communications."

The Pluralsight survey's authors made the following recommendations to executives who want to build a well-trained technical and business workforce:

* Consider upskilling versus outsourcing for AI capabilities - "Eighty percent of executives and 72% of IT practitioners agree their organization often invests in new technology without considering the training employees need to use it," the Pluralsight survey suggests. "Finding AI experts in the market is a gamble. Organizations that develop AI talent from their existing workforce will build the exact AI skills they need while providing valuable professional development opportunities to their teams."

* Develop an AI training strategy before implementing AI applications - "Organizations that want to take advantage of emerging technologies don't always have time to train their employees first. But if they can implement an upskilling strategy before deploying AI technology, their teams can start driving value from day one."

* Assess current AI capabilities - "Organizations need visibility into their teams' AI capabilities. Once they understand their strengths and weaknesses, they can develop an upskilling program that fills in the gaps and gives them the skills they need to use AI tools effectively."


Source: https://www.zdnet.com/article/how-to-avoid-the-headaches-of-ai-skills-development/


27
AI and climate: Tackling challenges and embracing change with a people-centered approach



Photo: Starmarpro/Adobe Stock (Generated with AI)

In May 2023, a World Bank team visited Secunda, a South African town defined by Sasol's unique commercial coal-to-liquids facility, to participate in a workshop on just green transition in Mpumalanga's coal-rich region. During the workshop, diverse voices from community leaders and global experts discussed the monumental challenges of a green transition, a conversation echoing far beyond the borders of this small town.

In these discussions, one thing became crystal clear: this transition is more than a simple technological swap from coal to green energy sources. It's a narrative deeply rooted in human stories – involving livelihoods, communities, and an entire generation at a historical juncture.

And aren't we at a similar crossroads with Artificial Intelligence (AI)? Like climate change, AI represents another major shift that we must navigate collaboratively. These two shifts together will redefine our world in ways we are only beginning to understand.

Our experience addressing the climate transition offers crucial insights for the ongoing AI governance discussion. The key justice principles—distributive, procedural, and recognition—that guide climate action also apply to the AI transition.

How can we make the AI transition fair and inclusive?
Tackling climate change is not just about technology or finance; it’s fundamentally about people. For instance, in South Africa, coal-dependent communities are worried about their future, faced with unprecedented changes to their livelihoods and social cohesion. Here are three ways that we can ensure everyone is included:

1. Empowering through training and skilling

Implementing a proactive strategy for economic diversification, along with livelihood support and skills training, can transform challenges into opportunities – particularly if communities are steering this change. This is what we call “distributive justice”: turning the downsides of major shifts into new opportunities for those who stand to lose the most. A similar principle could also be applied to artificial intelligence. Goldman Sachs warns that AI tools, such as ChatGPT, could replace nearly one-fifth of jobs worldwide. During previous cycles of autonomation, blue-collar workers lost their jobs. Now, white-collar workers, particularly women, are vulnerable, as AI excels at cognitive tasks, fundamental to office work.

Following a distributive justice model, employees could be trained to manage AI systems, thereby boosting their productivity. A recent study with the Boston Consulting Group showed consultants using AI completed 12.2% more tasks, 25.1% faster, with 40% higher quality results than those without AI. The study also highlighted AI as a skill leveler, with the initially lowest-scoring consultants experiencing a 43% performance boost when using it.

Currently, it’s estimated that only 1 in 8 workers globally have the necessary green skills, despite the sector's employment of over 67 million in 2022, and 90% of women lack these skills. Collaborative efforts from governments, industries, and educational institutions are essential to bridge this gap.

Addressing AI skills development is key for distributive justice.  Programs like Microsoft's AI Skills Initiative are providing vital AI training to diverse populations, and AI-enhanced education can democratize top-tier learning, mitigating brain drain and boosting talent markets in developing economies.

2. Ensuring inclusivity by hearing every voice

This is what we got to witness in Secunda, and, more broadly, we work to ensure that communities are heard and are part of the designing of climate solutions like climate resilient infrastructure or extraction of green minerals. Moreover, AI and machine learning technologies can boost citizen engagement by rooting climate interventions in community experiences, and their use in climate finance directs funds to impactful projects, ensuring transparency and ‘green’ accountability.

In the AI transition impacting jobs, healthcare, and education, it's essential to include diverse voices in governance to ensure broad benefits.  Inclusivity in AI also entails enhancing community engagement and proficiency to safeguard trust and information integrity, vital in areas like climate justice.

3. Upholding dignity and equity for marginalized communities

Respecting the rights and values of diverse societal groups is also crucial in ‘just transitions,’ both climate and AI.  This highlights the dignity of every individual and addresses unique challenges faced by marginalized communities, and is precisely what we focus on in our work on social dimensions of climate change. We highlight how climate impacts disproportionately affect women and marginalized groups like Indigenous Peoples, further deepening societal inequalities. Emphasizing the importance of community engagement, we advocate for leveraging local knowledge to co-design effective, tailored solutions for climate mitigation and adaptation.

Researchers have uncovered instances of AI perpetuating algorithmic bias, such as facial recognition errors with certain racial and ethnic groups and AI resume-screening tools showing gender discrimination due to male-dominated training data. Addressing these issues calls for applying recognition justice principles.

Towards a just and sustainable future in the AI era
It’s crucial that our technological advancements not only uphold justice principles but also prioritize environmental sustainability, tackling the ecological impacts of increased computing essential for AI expansion.

We continue to learn valuable lessons from our journey towards a more livable planet. Now, as we embrace the AI revolution, let's apply the relevant lessons. In this new world of green practices and AI, together we can foster an environment where we all thrive collectively, united by principles of justice and fairness.

Source: https://blogs.worldbank.org/climatechange/ai-and-climate-tackling-challenges-and-embracing-change-people-centered-approach?cid=ECR_E_NewsletterWeekly_EN_EXT&deliveryName=DM213305


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AI software engineer can handle coding projects end-to-end

A new AI model has triggered unease in tech Twitter due to its astounding ability to write complex code, then scan any errors that may arise in compilation and automatically correct them – just like a human programmer would. The model, dubbed ‘Devin’ is developed by AI startup Cognition.

Backed by bigwigs like Peter Thiel’s Founders Fund, former Twitter exec Elad Gil, and Doordash co-founder Tony Xu, Cognition has secured $21 million in funding. And while AI coding assistants have been around for a while, including OpenAI’s celebrated Copilot, Devin purportedly raises the bar by taking on end-to-end development responsibilities.

If Cognition’s claims hold water, Devin could mark a shift in the world of AI-assisted coding. Rather than playing second fiddle to human developers, this AI seems primed to operate as a self-sufficient software engineer in its own right. According to the startup’s founder and CEO Scott Wu, Devin operates within a secure sandbox, planning and executing complex engineering tasks through common dev tools like code editors and web browsers.

All a human needs to do is feed Devin instructions via a chat interface. From there, the AI dynamically maps out a solution, gets its hands dirty writing the actual code, fixes bugs along the way, tests its work, and keeps the user updated in real-time. If the programmer spots any issues, they can simply message Devin to course-correct.

Wu demonstrated Devin’s impressive range in a blog post, from deploying web apps and websites to fine-tuning large language models using GitHub repos.


Perhaps its biggest feat, however, is its performance on the SWE-bench test which evaluates AI’s ability to resolve real open-source software issues from GitHub. Devin could solve 13.86% of these cases entirely independently compared to figures like 4.8% for Claude, 3.97% for a different AI called SWE-Llama, and 1.74% for GPT-4.

While Devin remains under wraps for now, Cognition hopes to make it available to select customers soon. The company seems to view coding as just the start too, suggesting it could leverage its core “long-term reasoning and planning” advances to create AI workers for other domains.

Source: https://indianexpress.com/article/technology/artificial-intelligence/cognitive-devin-ai-programer-9212134/lite/

29
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30
Generative AI / The New Era of Super-Exponential Growth
« on: March 13, 2024, 04:17:46 PM »
The New Era of Super-Exponential Growth

KEY POINTS

1. "Stacked AI innovation" drives super-exponential technological growth and industry transformation.
2. AI evolves to solve problems autonomously and intuitively, marking a significant leap in capability.
3. Progress relies on adaptation to AI's transformative potential, shaping innovation and opportunities.


Just when you caught your breath, a new era is emerging—one that transcends the familiar bounds of exponential growth to venture into the breathless territories of super-exponential acceleration. This seismic shift is largely propelled by the profound and relentless force of artificial intelligence (AI), a catalyst setting the stage for unprecedented transformations across the spectrum of human endeavor. It's crucial to delve into what I term "stacked AI innovation" and the broader implications for the future of technology, society, and global economic growth.

The Path of Stacked AI Innovation

At the heart of this technological renaissance is the idea of stacked AI innovation, a concept that may need redefining in the context of artificial intelligence. Gone are the days when AI was merely a tool for processing and computation; today, AI stands as the architect of a new intellectual landscape, layering knowledge upon knowledge, insight upon insight. This is not merely AI assisting AI; it is AI exponentially enhancing its own capabilities, akin to a virtuoso musician who, having mastered one instrument, proceeds to orchestrate an entire symphony of innovation.

The trajectory of AI today sets a new benchmark, far surpassing the linear progression dictated by Moore's Law. We are witnessing the emergence of systems that are not just faster but inherently smarter and more adaptable, capable of learning from each iteration and evolving in real-time. This dynamic innovation propels us from a realm of predictable advancements to one of continuous, self-driven transformation.

The Far-Reaching Impact of AI's Evolving Mastery

The ramifications of stacked AI innovation are vast and varied, promising to be a potent catalyst across myriad industries. In finance, AI systems that commence with basic market analyses can evolve to predict intricate economic trends, thereby informing more strategic investment decisions. In transportation, AI can transition from optimizing individual routes to overhauling entire traffic management ecosystems, enhancing efficiency and safety in urban mobility.

This evolution of AI transcends mere data accumulation or algorithmic efficiency; it embodies AI systems developing an almost intuitive understanding of the tasks at hand. They are not simply problem-solvers; they are pioneers, identifying new challenges and devising innovative solutions. This leap from traditional machine learning to a self-evolving, insightful, and autonomous problem-solving dynamic marks the dawn of a new era in technological and intellectual advancement.

The Exponential Multiplier Effect

The true essence of stacked AI innovation lies in its exponential multiplier effect. Each layer of learning and adaptation does not merely add to the AI's capabilities; it magnifies them, enabling quantum leaps in understanding and application. This signifies a fundamental shift in our approach to addressing challenges and seizing opportunities across various sectors, positioning AI as the central driver of our collective quest for progress and innovation.

Collaborative Adaptation: The Path Forward

The key to unlocking AI's full potential lies in our collective ability to collaborate and adapt. This journey with AI is not a solitary venture but a collaborative expedition that demands the convergence of diverse minds from academia, industry, and government. Such a collaborative ecosystem ensures the development of AI in a manner that is both beneficial and ethical, catering to societal needs while promoting sustainable progress.

Adapting to an AI-enhanced world necessitates a cognitive shift—a willingness to embrace continual learning and change. As AI reshapes various facets of our existence, from our professional lives to our approach to global challenges, maintaining an informed and flexible mindset is paramount. Embracing AI entails recognizing it as more than a technological breakthrough; it is a transformative force that, when wielded responsibly, can harmonize with and amplify our shared aspirations and values.

In this new era of super-exponential growth, we are not merely spectators of technological advancement; we are active participants, shaping a future that mirrors our collective vision of progress and innovation. As we forge ahead, it will serve us well to embrace the transformative power of AI with both foresight and responsibility, steering the course of this extraordinary journey towards a future breathless with limitless possibilities.

Source: https://www.psychologytoday.com/us/blog/the-digital-self/202403/the-new-era-of-super-exponential-growth





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