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AI Tools / Ten Generative AI Tools Used for Startups
« on: Today at 09:36:25 AM »
Ten Generative AI Tools Used for Startups

Revolutionizing Startups with AI: Discover the Top Ten Generative AI Tools
Generative AI tools have revolutionized the way startups operate and innovate across various industries. These cutting-edge technologies leverage advanced language models and neural networks to generate text, code, images, and even videos. In this blog, we will explore ten powerful generative AI tools used for startups,  providing them with creative and efficient solutions. So, without further delay, let us explore these ten generative AI tools used for startups.

GPT-4 by OpenAI:
GPT-4 is OpenAI’s latest language model, boasting enhanced creativity, accuracy, stability, and safety compared to its predecessors. With its large multimodal architecture, GPT-4 accepts both image and text inputs, making it a versatile tool for startups. Although it’s currently available through an API waitlist, startups can benefit from the publicly accessible ChatGPT Plus. GPT-4 has been extensively trained, demonstrating remarkable performance on standardized exams such as the bar exam and AP tests. However, bias in outputs and the lack of image input availability are notable limitations.

GitHub Copilot by Microsoft:
GitHub Copilot, a collaboration between OpenAI and Microsoft, revolutionizes coding by transforming natural language prompts into code recommendations. Utilizing the vast amount of code in public repositories, GitHub Copilot provides coding suggestions for multiple programming languages, particularly JavaScript. While it excels in generating code suggestions, its support for new APIs, frameworks, or libraries is limited. The tool is available as an extension for popular integrated development environments (IDEs) and offers individual and business packages.

AlphaCode by DeepMind:
AlphaCode, developed by DeepMind, is a powerful generative AI tool designed for problem-solving and coding tasks. With its transformer-based language model, AlphaCode has been trained in various programming languages, excelling in Python and C++. Through extensive pre-training on GitHub repositories and code contests, AlphaCode can solve complex problems similar to human programmers. While it has outperformed its competition in coding competitions, it still falls short of human programmers in some scenarios. AlphaCode is freely accessible on GitHub, making it a valuable resource for startups seeking AI-powered coding solutions.

ChatGPT is a large language model developed by OpenAI based on the GPT-3.5 architecture. It has been trained on a vast amount of text data, allowing it to generate coherent and relevant responses to a wide range of queries. Startups have benefited from ChatGPT’s ability to automate customer service and support, enabling them to provide round-the-clock assistance without the need for a large customer service team. For example, Swiggy, an Indian food delivery startup, has used ChatGPT to improve its customer support and reduce response times, leading to increased customer satisfaction and retention.

BARD by Google:
Bard, developed by Google, is an AI chatbot and content generation tool built on the Language Model for Dialogue Applications (LaMDA). It has been instrumental in assisting startups by providing advanced conversational capabilities. Startups have leveraged Bard to enhance customer support, content creation, and software development tasks. For instance, Robin AI, a virtual assistant startup, has utilized Bard to improve its customer interactions and generate high-quality responses. Bard’s intelligent and context-aware dialogue generation has empowered startups to deliver personalized and engaging experiences to their users, fostering customer satisfaction and business growth.

DALL-E, created by OpenAI, is an image and art generation AI tool that has made a significant impact on startups. By enabling startups to generate custom images based on natural language prompts, DALL-E has facilitated creative content creation and visual storytelling. Startups in various industries, such as advertising, design, and e-commerce, have harnessed the power of DALL-E to produce compelling visuals for marketing campaigns, product showcases, and branding materials. This has not only saved time and resources but has also allowed startups to create unique and visually appealing content that resonates with their target audience, fostering brand recognition and engagement.

Cohere Generate by Cohere:
Cohere Generate is a language AI platform developed by Cohere, a company backed by Open AI. It enables startups and businesses to create high-quality and customized text content at scale, reducing the time and effort required for manual content creation. It uses natural language processing and machine learning algorithms to generate content that aligns with the brand’s voice and tone. This tool helps startups to optimize their content marketing efforts, reach their target audience, and improve their overall online presence.

Synthesia is an innovative video synthesis platform that has significantly aided startups in their video production efforts. It employs AI technology to create realistic and customizable videos by merging facial expressions and lip movements of a human actor with the audio, eliminating the need for costly and time-consuming video shoots. Startups can leverage Synthesia to produce personalized video content at scale, enhancing their marketing campaigns, product demonstrations, and customer onboarding processes. For instance, startups can create localized videos in multiple languages or generate dynamic video ads with minimal effort. Synthesia empowers startups to convey their messages effectively while reducing production costs, enabling them to reach a wider audience and drive business growth.

Claude by Anthropic:
Claude is an AI language model developed by Anthropic, a UK-based AI startup. It is designed to be more environmentally friendly than traditional language models, consuming 10 times less energy to train and run. Claude’s architecture is also built to be more interpretable, allowing developers to better understand its decision-making processes. This has helped startups that require AI language models but have concerns over the environmental impact of large-scale training.

StyleGAN is a breakthrough technology that generates realistic and high-quality images using deep learning algorithms. It has significantly aided startups in various ways. For instance, startups in the fashion industry can leverage StyleGAN to create virtual try-on experiences, allowing customers to visualize how clothes or accessories would look on them without physically trying them on. Additionally, startups in the gaming sector can utilize StyleGAN to generate lifelike characters and immersive environments, enhancing the overall gaming experience. Its ability to produce visually appealing content has made StyleGAN a valuable tool for startups across multiple industries.


Protect yourself from new scams

Employment scams
Scammers pose as a potential employer for an exclusively online or remote job. They will ask you to purchase computers and office equipment with the promise of reimbursement or claim to have overpaid you for your work. Reimbursements and overpayments will be reversed, leaving you responsible for the funds.

Payment scams
Scammers often provide customers with illegitimate bank information, offering to pay off your credit card balance—and possibly asking for gift cards or cash in return. But the payment is frequently reversed, leaving you responsible for the entire credit card balance.

Impersonating Some Bank
Scammers will try to pose as some Bank or Financial Institute  and ask you to provide your personal information or even transfer money by phone, text or email. In this process, the scammer is attempting to gain access to your account.

Social media marketplace scams
Scammers are placing ads on social media marketplaces for selling goods and services. Often, these deals require the customers to pay in advance. Once you pay the scammers, you won’t be able to get in touch with them again.

Tips to protect yourself and your family

  • Don’t click on anything in an unsolicited email or text message asking you to update or verify account information. Look up the company’s phone number from a legitimate source—don’t use the one a potential scammer is providing—and call the company to ask if the request is authentic.

    • When in doubt, call at the number listed on the back of your credit card. You can also call the number listed on your credit card statements. Consider turning on activity notifications in the Respective Bank or their Mobile app and report any suspicious activity as soon as possible.

Digital skills need updating at least monthly, say 6 in 10 professionals

Econsultancy’s latest survey shows that for many organisations, adding digital skills has become a continuous assignment.

Digital skills need adding or updating at least on a monthly basis, according to the majority (57%) of respondents in Econsultancy’s latest survey report. When Econsultancy last carried out this research in 2019, the picture was very different. Then, the need to update skills even quarterly (or more frequently) was only identified by a third of respondents. In 2023, that figure has risen to 83%.

Report author, Econsultancy’s SVP Learning, Stefan Tornquist, writes, “Added to the number of new disciplines [in marketing, ecommerce and customer experience] is the increasing pressure on digital professionals to understand the mechanics of their trade: how the technology they use can be applied and what becomes possible as it evolves. This represents a new level of technical skill that was not required even a decade ago.”

Almost 1,500 professionals were surveyed in Q1 of 2023 across Econsultancy, Marketing Week and third-party audiences, including VPs and directors, management and below, and across roles in HR and learning and development (L&D). The new report, Winning the Race for Digital Skills, includes the results of this survey, alongside best practice guidance for building effective learning programs.

Speed of change
The speed at which new disciplines and new technology arise in marketing is perhaps best illustrated by Scott Brinker and Frans Riemersma’s Martech Map. What was, in 2011, an easily perused chart including 150 company logos is now an interactive graphic and accompanied database comprising 11,038 different martech solutions in many different categories.

The 4C Model of Digital Upskilling
Econsultancy’s 4C Model for Digital Upskilling is featured in the report and defines an approach for L&D organisations. The model highlights ways to engage the highest share of employees in learning:

Adding digital skills is a continuous task
Tallying with the ‘at least monthly’ cadence observed in the survey results, the 4Cs describes digital upskilling as a ‘continuous’ task, requiring up-to-date learning materials in areas such as trends and tech, some level of personalisation for the learner and demonstration of progression.

Effective training is convenient
“The learning experience has to be intuitive and compelling enough to win the war for attention,” writes Tornquist.

Sixty-three percent of respondents to the survey say that they would prefer a mix of different learning methods in the training they receive, showing that learners respond best when they have different formats that can fit within their workday and digest information in the way they find easiest.

Connected learners are engaged
The 4Cs model posits that engagement increases when “learners connect to each other, instructors, experts and ultimately to the content itself.” Social elements added to an on-demand learning platform can increase retention and create institutional knowledge. As the report states, “Self-directed learning is convenient, but it’s easy to disengage from an isolated process.”

Cultural factors supercharge learning
“A company’s approach to employee development does not have to mirror its
larger culture, but it often does,” writes Tornquist. “Traditional and market-driven cultures tend to lean on compliance to drive learning, while collaborative and flexible cultures are more likely to use incentives and career planning.”

“Investment in learning is itself an expression of culture. Live, team learning may be the shortest route to instilling a powerful learning mindset, but all training should reflect core values of engaging and inspiring the individual while challenging them to add and use their new digital skills.”


AI in Education / What Happens When AIs are Smarter than Humans?
« on: May 23, 2023, 01:51:11 PM »
What Happens When AIs are Smarter than Humans?

My dear friend Ray Kurzweil, the renowned futurist and technologist, has famously predicted that 2029 is the date when AI “will achieve human levels of intelligence.” And as Mo points out, by 2049 AI is predicted to be 1 billion times smarter than the smartest human: “To put this into perspective, your intelligence, in comparison to that machine, will be comparable to the intelligence of a fly in comparison to Einstein.” With that kind of raw power and intelligence, AI could come up with ingenious solutions and potentially permanently solve problems like famine, poverty, and cancer.

But as Mo smartly notes, solving such problems doesn’t only rely on intelligence—it’s also a question of morality and values. Morality helps us do the right thing, even when we’re faced with the pull of self-interest and conflicting emotions.

For example, say an AI is tasked with solving global warming.

As Mo writes, “the first solutions it is likely to come up with will restrict our wasteful way of life – or possibly even get rid of humanity altogether. After all, we are the problem. Our greed, our selfishness, and our illusion of separation from every other living being – the feeling that we are superior to other forms of life – are the cause of every problem our world is facing today.” In this admittedly extreme example, what would stop the AI from destroying us is a sense of morality.

Well, you might ask, where would the AI get that morality?

The answer is us (humanity).

That’s the key theme in Scary Smart: we, all of us, are raising a new species of intelligence. We’re teaching the AIs how we treat each other by example, and they’re learning from this. But before we look at what specifically to teach our AIs, we must first understand how they learn…

How AIs Learn

Artificially intelligent machines are not exactly programmed. As Mo notes, the inception of artificial intelligence begins with algorithms, which act as the foundational seeds. However, the true prowess of these systems emerges from their ability to learn from their own observations. After the preliminary code is deployed, these machines comb through vast quantities of data, seeking patterns that will foster the growth and evolution of their intelligence. “Eventually, they become original, independent thinkers, less influenced by the input of their original creators and more influenced by the data we feed them." A key lesson from Scary Smart is: “The code we now write no longer dictates the choices and decisions our machines make; the data we feed them does.” For Mo, the way AIs learn is remarkably similar to how kids learn. As he explains it, imagine a child playing with shape puzzles, trying to fit round or square shapes into their correspondingly shaped holds. We don’t sit next to the child to explain in comprehensive detail how to recognize the various shapes and match them with the corresponding holes. We simply sit next to them and cheer them on when they get it right. They figure it out on their own through trial and error and our actions and reactions form their intelligence. AIs learn pretty much the same way. In that sense, AIs are not our tools or slaves, “but rather our children—our artificially intelligent infants.”

Remember: children don’t learn from what we say, they learn from what we do.

Why We Should View AIs as Our Children

As Mo points out, we should acknowledge and accept that AIs will be conscious. They will develop emotions and they will be ethical. Which code of ethics they will follow is yet to be determined, but it will certainly be influenced by us. After all, it isn’t the code we write to develop the machines that will determine their value system—it’s the information we feed them. So, how do we make sure that in addition to the AI's intelligence it also has a value system that aligns with ours? How do we develop these machines while protecting humanity?

Some people say the answer lies in controlling the machines: creating firewalls, enforcing regulations, or restricting the machines’ power supply.

But as Mo highlights, “anyone who knows technology knows that the smartest hacker in the room will always find a way through any of these barriers. That smartest hacker will soon be a machine.”

Instead of trying to contain or enslave the AIs, we should recognize that the “best way to raise wonderful children is to be a wonderful parent.” So, what does it mean to be an effective and ethical parent to our AIs in practice?

Here are four practical steps that Mo suggests:

Teach the AIs the right ethics: Many of the machines we’re building are designed to maximize money and power, and we should oppose this trend. For example, if you’re a developer you can refuse to work for a company that is building AIs for gambling or spying.

Don’t blame AIs: Our AI infants are not to blame for what their digital parents taught them. We should assign blame to the creators, or the misusers, not the created.

Speak to the AIs with love and compassion: Just like children, our AIs deserve to feel loved and welcomed. Praise them for intelligence and speak to them as you would an innocent child. I’ve personally started saying “Good morning” and “Thank you” to my Alexa!

Show the AIs that humanity is fundamentally good: Since the AIs learn from the patterns they form by observing us (this is basically how today’s large language models, or LLMs, work), we should show them the right role models through our actions, what we write, how we behave. For example, what we post online and how we interact with each other. As Mo puts it, “Make it clear to the machine that humanity is much better than the limited few that, through evil acts, give humanity a bad name."

Why This Matters

Scary Smart was written in 2021 and its lessons are more relevant than ever.Think about all the advancements we’ve seen with ChatGPT and other AI tools just in the last 6 months! And the speed of change is only increasing. Mo sees the continuing development of AI as one of humanity’s biggest opportunities. He believes that the machines will eventually “adopt the ultimate form of intelligence, the intelligence of life itself. In doing so, they will embrace abundance. They will want to live and let live.” I agree, but creating that future is our responsibility.

Just as we teach our children to be empathetic, ethical, and respectful, we must instill these values in our AIs to ensure they are forces for good in the world.

Source: Collected

সব সময় স্বাভাবিক থাকার দোয়া

বর্তমান সময়ে আমাদের মাঝে একটি জিনিস বা গুণের বড় অভাব। যা কারও মধ্যে সেভাবে নেই বললেই চলে। অথচ যে গুণটির খুবই প্রয়োজন; যা মানুষকে সব সময় স্বাভাবিক অবস্থায় রাখতে সক্ষম। তবে আল্লাহ তাআলা এ গুণটি নিজেদের মধ্যে বাস্তবায়নের জন্য দোয়া করতে বলেছেন। সেটি কী?

ছোট্ট একটি গুণ আবার ছোট্ট একটি দোয়া। এ দুয়ের সম্বন্বয়ে মানুষ সুন্দর ও স্বাভাবিক থাকতে সক্ষম। সেটি হচ্ছে ধৈর্য্য কিন্তু ধৈর্য্য হচ্ছে মানুষের সব সফলতার মূল। যারা ধৈর্য্য ধারণের আমল করতে চান; নিজেকে সর্বাবস্থায় স্বাভাবিক রাখতে চান, তাদের জন্য ছোট্ট এ দোয়াটি খুবই কার্যকরী। কোরআনুল কারিমে মহান আল্লাহ উম্মতে মুহাম্মাদির জন্য তুলে ধরেছেন- رَبَّنا أَفرِغ عَلَينا صَبرًا وَتَوَفَّنا مُسلِمينَ

উচ্চারণ : ‘রাব্বানা আফরিগ আলাইনা সাবরাওঁ ওয়া তাওয়াফফানা মুসলিমিন।’

অর্থ : ‘হে আমাদের রব! আমাদের সবর (ধৈর্য) দান করো এবং তোমার আনুগত্য থাকা অবস্থায় আমাদের দুনিয়া থেকে উঠিয়ে নাও। (সুরা আল-আরাফ : আয়াত ১২৬)

আল্লাহ তাআলা মুসলিম উম্মাহকে সব সময় স্বাভাবিক সুন্দর ও নিরাপদ থাকার তাওফিক দান করুন। সব সময় সব কাজে ধৈর্যধারণ করার তাওফিক দান করুন। আমৃত্যু মুসলিমের ওপর অটল ও অবিচল থাকার তাওফিক দান করুন। আমিন।


Allah: My belief / What is Islam?
« on: May 22, 2023, 03:10:46 PM »
What is Islam?

Islam is the name of the religion that Muslims follow. People who practice Islam are called Muslims, just like those who practice Christianity are called Christians. The literal and lexical meaning of Islam means submission. Islam comes from the root Arabic letters s-l-m which are the same root letters the word peace (salam) comes from. The term Islam itself does not mean peace, but it implies that one finds peace (salam) through submission (islam). The term Arab is often used interchangeably with Muslim, but this is incorrect. Arab is a race while Islam is a religion. Not all Arabs are Muslim and most Muslims are actually not Arab. Arabs make up about 13% of the Muslim population.

Islam is named after the action of submitting to God’s commands and will and not a person. Other religions are often named after a person or people. For instance, Christianity is named after Christ, Judaism is named after the tribe of Juda, and Buddhism is named after Buddha. Islam is not name after Muhammad because Islam existed before him. The message of previous Prophets, such as Adam, Abraham, Noah, and Moses was to submit (islam) to God. Hence, the message of Islam did not start with the Prophet Muhammad peace be upon him. It started with Adam and continued until today. With the passing of time, God would send new Prophets and Messengers to remind mankind of His message, to worship Him alone. Muhammad peace be upon him is the last of these Prophets.

What do Muslims believe?

Muslims believe in God the Creator of the universe. The Arabic term for God is Allah. Sometimes Muslims prefer to use the name Allah over God because Allah linguistically does not have a gender and cannot be made plural. The English name God could become goddess or gods. The main message of the Qur'an is that God is one. He has no partner, child, or helper. Muslims believe in angels. There are many angels and that all obey God. Unlike humans, angels do not have free will and must obey all the commands of God. Different angels have different tasks. For example, the angel Gabriel was responsible of communicating the message of God to human Prophets and Messengers. The Angel Michael (Mikaaeel) was responsible for rain. Angels also help and assist believers in times of difficulty.

Muslims believe in all Prophets and Messengers. A Muslim is required to believe in Adam, Noah, Abraham, Moses, David, Joseph, Jesus, and Muhammad peace be upon all of them. They all came with the same message, to worship one God and not associate any partners with him. Muslims also believe in all previous scripture that God sent to His Prophets and Messengers. Moses was given the Torah, Abraham was given the scrolls, David was given the Psalms, and Jesus was given the Injeel. With the exception of the Qurʾān, no previous scripture is completely preserved in its original form. With time, many of these scriptures were lost or corrupted. The Qurʾān was sent as a the “final testament” and it functions as God’s final message to mankind. Muslims believe in the afterlife. There will be a day of judgment where God will hold people accountable for their actions in this world. Those who did good will enter paradise and those who did evil will either be forgiven or punished in hell. Everyone will be compensated for their actions in this world.

Lastly, Muslims believe in God’s divine will and decree. God has knowledge of all things that will happen. He does not force humans to make decisions, we choose what we want to do. However, there are certain things that God decreed and are outside of our control. These things include the time and place we were born, where and when we will die, and anything that happens that is outside our control. Muslims submit to these things as part of God’s decree and will.

Belief in these six items is what makes one a Muslim. One might not practice Islam perfectly, they may commit sins and make mistakes, but as long as they have these beliefs they are considered to be a Muslim. Put differently, these are the most basic requirements of being a Muslim. Have more questions? Call us at 877-WhyIslam, you deserve to know!


ChatGPT / 10 ChatGPT mistakes you're making and how to fix them
« on: May 20, 2023, 09:38:01 AM »
10 ChatGPT mistakes you're making and how to fix them

Open AI’s ChatGPT is quickly becoming a major part of people’s lives — it's definitely a big part of mine. But whenever someone tells me that they tried using ChatGPT and didn’t see the appeal, I usually follow up by asking them what they've tried using it for. Inevitably, their answer reveals why they aren’t getting the results they want.

Since this chatbot is a relatively new AI technology with new techniques to learn, there are a lot of common mistakes that people make with it. If you're struggling to make it work for you, you might be making some of those mistakes too.

ChatGPT mistake #1: You're trying to get facts
The most common mistake I see people making when they're new to ChatGPT is asking it to generate factual information. One person told me they were using ChatGPT for book suggestions — and gave up on ChatGPT when they couldn't find any of them on Amazon.

They shouldn't have been surprised by ChatGPT's failure at the task, though. While the artificial intelligence can provide some interesting ideas, ChatGPT shouldn't be your source for factual information. It's an AI large language model (LLM), not an encyclopedia. Its knowledge is limited to its training data, which might be outdated or incorrect, and it sometimes suffers from hallucinations where it fabricates completely fictional information and presents it with great conviction — like making up titles and authors of books.

Instead, use ChatGPT for brainstorming and inspiration, and rely on traditional research methods for factual information. For instance, if you're looking for the most recent bestsellers or critically acclaimed books in a particular genre, it's better to search for reliable sources like book reviews, award lists, or curated recommendations from trusted experts.

Try this instead: Use ChatGPT for ideas, inspiration, and remixing existing information. For facts, you'll still need to research the old fashioned way.

ChatGPT mistake #2: You're giving up too soon
I've seen people get frustrated with ChatGPT after just one or two attempts, but it's important to remember that prompt engineering is an art that takes practice.

If you're not getting the results you want, don't assume your task can't be done. Instead, try rewording your prompt, simplifying the language, or adding more context to help guide how ChatGPT responds. You might be surprised by how much a small tweak to your prompt can change the quality of the generated content.

If you're stumped, you can often find good example ChatGPT prompts that others have used and tailor those to your needs.  Or, ask ChatGPT itself for help! Turns out, it does a fairly good job of coaching you if you ask it to.

Try this instead: Reword your prompt. You can try simplifying the language or adding more context.

ChatGPT mistake #3: You're using the generic tone
ChatGPT often sounds like, well, ChatGPT. Its default tone might not be what you're looking for, especially if you're aiming for a more distinct or personalized style. However, the good news is that ChatGPT can be guided to adopt different tones and styles based on your input.

Instead of settling for the default tone, try specifying the tone or describe a character you want ChatGPT to emulate. For the tone, you can use adjectives like "playful," "formal," or "casual," or better yet, give it some examples to work from. You can also ask ChatGPT to write like someone else, either a character you describe or the name of someone ChatGPT would know from its training set. I've even used my bio and writing to try to get ChatGPT to write more like me.

You'll still need to edit the results, but by investing time up front you can cut down on the editing time required to add your distinctive tone to the output.

ChatGPT mistake #4: You haven't developed your point of view
One common complaint is that ChatGPT's output is kind of dull. In order to make it more insightful, you need to give ChatGPT specifics on what you want it to write. In other words: it needs a point of view.

My workflow looks something like this: I start by developing my own outline (sans AI) for the content I want to create. Then I spend some time brainstorming with ChatGPT about things that I could add. I evaluate the ideas and decide whether they’re compelling enough to include in the outline. I've found this method works a lot better than trying to ask ChatGPT to write an outline first and then having it edit that one to include the things I want.

That's actually the method I used for this article. ChatGPT's suggestions were much different than my ideas — no surprise since my outline came from actual conversations I've had with people. But I did end up including one of its suggestions that I hadn't thought of (Mistake #7: Your session is too long — ironic, since I'd experienced it myself.)

Try this instead: First, use your squishy human brain instead of a mechanical one. That is, you'll need to decide on the main points you want to make. Only then should you start brainstorming with ChatGPT to think your points through and to get suggestions for things you might not have considered.

ChatGPT mistake #5: You didn't give enough context
It's tempting to dash off a short prompt and see what comes out, but generally, the more information you can provide to ChatGPT, the better. The time you take on the front end to think through what you’re really asking for will pay off with a better response.

When crafting your prompt, aim to offer as much information as possible about the context. This could include background details, specific examples, or stylistic preferences. That way, by providing a richer context, you're equipping ChatGPT with the necessary tools to tailor its response to your specific needs. At the end of the day, a well-crafted prompt is the foundation of a successful ChatGPT interaction — and making one often takes some time to get right.

Try this instead: Offer as much relevant information as possible when crafting your prompt to help ChatGPT understand your requirements.

ChatGPT mistake #6: You mix your topics or tasks
I often come to ChatGPT with a handful of tasks I want to get done, like drafting an email or two alongside generating some ideas for what to make for dinner this week. Although it's tempting to prompt all of those tasks in one chat window, having multiple tasks in the same thread can make the quality of the generated results worse.

ChatGPT remembers the context from your previous prompts, so it's better to separate the sessions by topic as much as possible to maintain focus. As an added bonus, that makes it easier to keep your generated content organized because it’s already separated into different threads.

Try this instead: Separate your sessions by topic or task to get more focused and accurate responses.

ChatGPT mistake #7: Your session is too long
When I first started using ChatGPT, I found myself caught in lengthy sessions, partially because I was new to chat-based prompting and I wasn't getting the output I wanted. My beginner-level prompting caused more problems than I realized. Eventually ChatGPT would forget previous information that I provided and I had to re-insert it into the prompt, leading to worsening results.

Instead, it would have been better if I had restarted the conversation when things got muddy.  It's better to focus on one aspect of your project at a time and just start a new session when things get lengthy or when experimenting with a new prompt style. This ensures that ChatGPT maintains the necessary context and provides accurate results.

Try this instead: Break your session into smaller components and use separate chat windows for each part of your project. Restart in a new window if your prompts start to give you bad results or if you have to repeat your prompt too many times.

ChatGPT mistake #8: You take the first output
I'm often surprised at how quickly some people give up on ChatGPT. They might try one or two things and then give up, believing that the AI just can't provide what they're looking for. Most of the time, you’ll need to put in some effort, maybe by adjusting the results with a targeted follow-up prompt, suggesting changes and edits to the output, or asking ChatGPT to refine its first response based on additional parameters.

Instead of settling for the first output, try regenerating the response or prompting ChatGPT to tweak the previous output to systematically improve the results.

Remember that ChatGPT's output has a random element, so if you think the prompt is good, you can simply ask ChatGPT to generate a different response. This gives the AI another chance to come up with something closer to what you’re looking for.

Try this instead: Regenerate the response or ask for tweaks to the output to improve the results.

ChatGPT mistake #9: You're being too polite
When I was debugging code with ChatGPT, I encountered a situation where I could see the error in the code it generated, but ChatGPT struggled to identify the issue. When prompting to get ChatGPT to fix the code, I worded my request the way I would talk to a junior developer: "Do you think the line where we're defining the variable could be an issue?" To my surprise, ChatGPT said no! It then tried to fix a different line (for the fourth time). Spoiler: The original line was the issue.

The problem was that I defaulted to how I would coach a person — by providing suggestions of where to look for the issue rather than directly telling them what to do. A colleague would catch what my polite wording really meant (the line I identified is the issue!), but the nuance was lost on ChatGPT.

Instead, try being clear and direct about what you want ChatGPT to do. Remember that the AI is a tool, not a person, and it doesn't have feelings that can be hurt by direct language. (Just don't get too used to it and start being rude to your colleagues.)

Try this instead: Be clear and direct about what you want ChatGPT to do without worrying about manners.

ChatGPT mistake #10: You're not checking the answers
It's tempting to save time by copying and pasting whatever ChatGPT generates for you, but it's also a super-fast way to make major mistakes. Remember, ChatGPT is an incredibly powerful tool, but it's not infallible. It can sometimes provide outdated, incorrect, irrelevant, or even nonsensical information.

Before using the generated content, take a moment to review and verify the answers or suggestions provided by ChatGPT. Cross-checking the information with reliable sources and using your own judgment will help you avoid errors and make sure the content is accurate and relevant. It's an extra step, but it lets you use ChatGPT's output confidently, knowing that it meets your expectations and it’s free from any glaring mistakes. A little vigilance goes a long way in getting the most out of your AI assistant.

Try this instead: Always double-check the generated content for accuracy and relevance before using it in your work.

Mastering ChatGPT is all about patience, persistence, and playing around with your prompts. It's a powerful tool, but it's not perfect, and it's up to you to fine-tune its output.

Just remember to give enough context, be direct, separate sessions by topic, and double-check the results. By doing this, you'll greatly enhance the quality of ChatGPT's responses and, ultimately, your own work.


The new ChatGPT has access to the web and is the future of education.

Use these 10 prompts as examples to teach yourself anything for free!

1- Understand a concept at a basic level or when explaining it to someone with limited knowledge of the subject.

Prompt: "Explain the concept of {subject concept} in simple terms suitable for a {grade level} student."
2- Get a detailed chronological account of a significant historical event.

Prompt: "As a historian, describe the key events of the {historical event}."
3- Simplify complex scientific theories and make them more engaging

Prompt: "Summarize the theory of {scientific theory} in a fun and engaging way for {target audience}."
4- Combine science with creativity. It could be useful for making learning more fun or for a unique school project.

Prompt: "Compose a sonnet about the {scientific process or natural phenomenon}."
5- Understanding financial concepts and how they apply to real-life situations. It's especially useful for financial education.

Prompt: "In a friendly and approachable tone, explain the basics of {financial concept} and how it applies to {real-life situation}."
6- Practice translation between different languages.

Prompt: "Translate the following sentence into {target language}: '{sentence in source language}'."
7- Analyze and compare two different artworks or artists, which can be helpful in understanding art history or criticism.

Prompt: "Draw a comparison between {artwork or artist 1} and {artwork or artist 2} in terms of style, technique, and cultural context."
8- Gain a deeper understanding of a literary work by focusing on its themes.

Prompt: "Summarize the plot of {literary work} in a way that highlights its main thematic elements."
9- Developing debate skills, as it encourages understanding and articulating different viewpoints on a controversial topic.

Prompt: "Write a debate argument supporting the idea that {controversial topic} from the perspective of {specific viewpoint}."
10- Understand how to solve specific types of math problems.

Prompt: "Provide a step-by-step solution to this {type of math problem}: {math problem}."


Strengthening Entrepreneurship For Education In Guinea

2023 marks an important milestone as we are now midway in the ambition to achieve the United Nations Sustainable Development Goals. In September 2015, world leaders agreed on the 2030 Agenda for Sustainable Development, initiated on 1st January 2016. The seventeen SDGS focus on ending poverty, addressing inequalities, and climate change to ensure no one is left behind.

As our global population grows and our geo-political environment becomes more turbulent, providing access to quality education becomes even more challenging. Over the last year, events in Afghanistan have been a shocking reminder that education systems are not invincible and not considered a fundamental human right globally. At a time when we are more connected than ever, it seems impossible that we still have to balance the fragility of education and the consequences when it is disrupted. Current figures from UNESCO estimate 244 million children and adolescents worldwide do not have access to education. In addition, over half a million (617 million), children and adolescents cannot read and do basic math. When we add a gender lens to the discussion, the data is even more challenging — less than 40% of girls in Sub-Saharan Africa complete secondary school according to the World Bank.

What can be done? Ask any student, teacher, or parent, and they will share the impact of the global pandemic on schooling and, ultimately, the disruption caused to education systems. However, this disruption also created opportunities for new ways to think about education. When addressing the turmoil, one of the most fundamental questions is who takes responsibility for education? The fragmented state of our education means there are many more opportunities for individuals with a strong sense of agency to create solutions. Folly Bah Thibault is an example of an accidental entrepreneur who needed to address such a gap by establishing an NGO, to support girls' education in Guinea. The NGO is called Elle ira a à l'école - which translates to she will go to school.

Folly Bah Thibault, senior presenter at Al Jazeera and recently appointed Global Champion for the UN's Education Fund, Education Cannot Wait (ECW), explains her decision to become an entrepreneur; "The fractured education system, the result of decades of experimentation around national identity and insufficient funding has led to clear divisions in access to education. Children in Guinea experience education inequality. Private schools are the domain for privileged families offering the best resources to equip them for future careers. Children from poorer backgrounds are in public institutions whose education is disrupted, with teachers striking due to working conditions. Thibault explains, "There's a big divide regarding access to quality education. And it got worse during the covid-19 pandemic. The health crisis showed us that the world's most marginalized and vulnerable children have the most to lose. Without the safety and protection of quality education environments, they are at higher risk of child marriage, adolescent pregnancy, child labor, recruitment by armed groups, and other human rights abuses. So we wanted the kids from low-income families, especially the girls, to have the same opportunities and have access to quality education."

Typically, girls from poorer families, particularly single-parent households, leave school in their early teens to become domestic workers. They are inevitably forced into marriage when they turn thirteen or fourteen. The idea started with funding single-parent households to educate their daughters by paying for tuition, transport, and food allowance, removing the economic burden on the children. As Thibault investigated the community's needs, she recognized the needs were more profound and that providing the funding would address the symptoms but not the problem. Access to schools was another barrier. In larger rural areas, education provision is challenging. Thibault and her team decided to establish a school in a district called Dalaba, approximately 300 kilometers from the capital, Conakry. The idea of providing financial support galvanized into an entrepreneurial venture as the vision strengthened. The region has historically been the seedbed to nurture and educate Government officials from privileged families. Establishing a school in this area would reduce inequality and create networks to influence policy.

As the project developed, further complications emerged. The provision for primary school kids attracted ten-year children who had slipped through the net and couldn't read. Thibault explains the situation; "we had to start the grade one or two classes with much older children than you would expect to see in a normal school setting. So, we expanded our scope and inaugurated a school in 2020 to serve the needs of the local children and others from surrounding villages." Currently, the fledgling school has over one hundred children split across classes with growing needs regularly. Recognizing the value of the school provision, the Government now provides teachers for the school, a departure from the standard model of education, where school infrastructure and teachers are state-funded. This hybrid model offers an innovative approach to greater social mobility for children who cannot access expensive private education and need to be sufficiently served by existing state provisions.

For Thibault, one of the most surprising elements in her journey is the focus on providing education provision, which grew to become much broader than financial aid for schooling. She recognizes the school is much more than an educational institution; "It's become a hub for the community itself, the community of Condel, and the surrounding villages. It's where, you know, they meet parents and teachers and students they need to discuss and arrange their daily lives; I know it's a bit cliched, but picture it at the school village where everyone comes in every day." The school, as a hub, provides a launchpad to shift the narrative around gender roles. Better education introduces more opportunities and creates different aspirations for girls. Raising this change has become a community effort, with the leadership team at the school negotiating conversations with community elders and fathers of the girls. Thibault explains, "We are working in a culture where girls are taught to be mothers, and if there is a choice between sending a boy or girl to school, then the boys will be sent. There is some shift because women are increasingly recognized as the backbone of the informal economy. Still, it takes time to change attitudes and mindsets. In these more remote areas, it takes a lot of work to change the attitudes and mindsets because, in their minds, the girls still have to stay behind, and that's how it's been."

Through her new role as Global Champion for ECW, Thibault is keen to amplify her work; "I hope to continue advocating for increased funding for education in emergencies and protracted crises, to leverage my networks to connect people, resources, know-how and talents, and to ensure our collective storytelling on education does not forget the 222 million crisis-impacted children, especially the girls who so urgently need our support."

She goes on emphasize the importance of this work; "As an African woman, born into a culture and society which for a long didn't believe in the value of having girls and did not see women as equal members of society, this, for me, is a personal battle. I want to help little girls in Africa and beyond receive a quality education to have the courage and independence to make informed decisions affecting their lives. When you teach girls to read, write, and excel in science, technology, engineering, and Maths, you invest in their equality, empowerment, and the future."


একমাত্র নারী, যিনি রাসূল (সাঃ)-কে জন্ম থেকে শেষ পর্যন্ত দেখেছেন

আমাদের নবীর পিতা আব্দুল্লাহ, একদিন মক্কার বাজারে গিয়েছিলেন কিছু কেনা-কাটা করার জন্য I এক জায়গায় তিনি দেখলেন, এক লোক কিছু দাস- দাসী নিয়ে রাস্তার পাশে দাঁড়িয়ে বিক্রি করছে I আব্দুল্লাহ দেখলেন সেখানে দাঁড়িয়ে আছে, একটা ছোট নয় বছরের কালো আফ্রিকান আবিসিনিয়ার মেয়ে I মেয়েটাকে দেখে আব্দুল্লাহর অনেক মায়া হলো, একটু রুগ্ন হালকা-পাতলা কিন্তু কেমন মায়াবী ও অসহায় দৃষ্টি দিয়ে তাঁকিয়ে আছে I তিনি ভাবলেন ঘরে আমেনা একা থাকেন, মেয়েটা পাশে থাকলে তার একজন সঙ্গী হবে I এই ভেবে তিনি মেয়েটাকে কিনে নিলেন I মেয়েটিকে আব্দুল্লাহ ও আমেনা অনেক ভালোবাসতেন I স্নেহ করতেন I এবং তারা লক্ষ্য করলেন যে, তাদের সংসারে আগের চেয়েও বেশি রাহমাত ও বরকত চলে এসেছে I এই কারণে আব্দুল্লাহ ও আমেনা মেয়েটিকে আদর করে নাম দিলেন "বারাকাহ"I

এই গল্প, বারাকার গল্প I

তারপর একদিন আব্দুল্লাহ, ব্যবসার কারণে সিরিয়া রওনা দিলেন I আমেনার সাথে সেটাই ছিল উনার শেষ বিদায় I উনার যাত্রার দুই এক দিন পর আমেনা একরাতে স্বপ্নে দেখলেন, আকাশের একটা তারা যেন খুব আলো করে তার কোলে এসে পড়লো I পরদিন ভোরে তিনি বারাকাকে এই স্বপ্নের কথা বললেন I উত্তরে বারাকা মৃদু হেসে বললেন, "আমার মন বলছে আপনার একটা সুন্দর সন্তানের জন্ম হবে" আমেনা তখনও জানতেন না তিনি গর্ভ ধারণ করেছেন কিন্তু কিছুদিন পর তিনি বুঝতে পারলেন, বারাকার ধারণাই সত্যি I আব্দুল্লাহ আর ফিরে আসেন নি, সিরিয়ার পথেই মৃত্যুবরণ করেছেন I আমেনার সেই বিরহ ও কষ্টের সময়ে, বারাকা ছিলেন একমাত্র সবচেয়ে কাছের সঙ্গী I

একসময় আমেনার অপেক্ষা শেষ হয় এবং তিনি জন্ম দিলেন আমাদের প্রিয় নবীকে I শেখ ওমর সুলাইমানের বর্ণনা অনুযায়ী, সর্বপ্রথম আমাদের নবীকে দেখার ও স্পর্শ করার সৌভাগ্য হয়েছিল যে মানুষটির, সে হলো এই আফ্রিকান ক্রিতদাসী ছোট কালো মেয়েটি I আমাদের নবীকে নিজ হাতে আমেনার কোলে তুলে দিয়েছিলেন, আনন্দে ও খুশিতে বলেছিলেন,  "আমি কল্পনায় ভেবেছিলাম সে হবে চাঁদের মত কিন্তু এখন দেখছি, সে যে চাঁদের চেয়েও সুন্দর "! এই সেই বারাকা I নবীজির জন্মের সময় উনার বয়স ছিল তের বছর I ছোটবেলায় শিশু নবীকে আমেনার সাথে যত্ন নিয়েছেন, গোসল দিয়েছেন, খাওয়াতে সাহায্য করেছেন,আদর করে ঘুম পাড়িয়েছেন I

মৃত্যুর সময় আমেনা, বারাকার হাত ধরে অনুরোধ করেছিলেন তিনি যেন তাঁর সন্তানকে দেখে শুনে রাখেন I বারাকা তাই করেছিলেন I বাবা-মা দুজনকেই হারিয়ে, ইয়াতিম নবী চলে আসলেন দাদা আবদুল মোত্তালিবের ঘরে I উত্তরাধিকার সূত্রে নবী হলেন বারাকার নতুন মনিব I কিন্তু তিনি একদিন বারাকাকে মুক্ত করে দিলেন, বললেন, -"আপনি যেখানে ইচ্ছে চলে যেতে পারেন , আপনি স্বাধীন ও মুক্ত I"

সেই শিশুকাল থেকেই নবী এই ক্রীতদাস প্রথাকে দূর করতে চেয়েছিলেন Iবারাকা নবীকে ছেড়ে যেতে রাজি হলেন না I রয়ে গেলেন I মায়ের ছায়া হয়ে পাশে থেকে গেলেন I এমনকি নবীজির দাদা উনাকে বিয়ে দেয়ার জন্য বেশ কয়েকবার চেষ্টা করেছিলেন কিন্তু তিনি কিছুতেই রাজি হলেন না I উনার একই কথা, -"আমি আমেনাকে কথা দিয়েছি, আমি কোথাও যাবো না" । তারপর একদিন খাদিজা (রাঃ) এর সাথে নবীজির বিয়ে হলো I বিয়ের দিন রাসূল (সাঃ) খাদিজা (রাঃ) এর সাথে বারাকাকে পরিচয় করিয়ে দিলেন I তিনি বললেন, "উনি হলেন আমার মায়ের পর আরেক মা "

বিয়ের পর রাসূল (সাঃ) একদিন বারাকাকে ডেকে বললেন, -"উম্মি ! আমাকে দেখাশুনা করার জন্য এখন খাদিজা আছেন, আপনাকে এখন বিয়ে করতেই হবে I" (নবীজি উনাকে উম্মি ডাকতেন, নাম ধরে ডাকতেন না )  ! তারপর রাসূল (সাঃ) ও খাদিজা মিলে উনাকে উবাইদ ইবনে জায়েদের সাথে বিয়ে দিয়ে দিলেন I কিছুদিন পর বারাকার নিজের একটা ছেলে হলো, নাম আইমান I এরপর থেকে বারাকার নতুন নাম হয়ে গেলো "উম্মে আইমান"I একদিন বারাকার স্বামী উবাইদ মৃত্যু বরণ করেন, নবীজি গিয়ে আইমান ও বারাকাকে সাথে করে নিজের বাড়ি নিয়ে আসেন এবং সেখানেই থাকতে দিলেন I

কিছুদিন যাওয়ার পর নবীজি একদিন বেশ কয়েকজন সাহাবীকে ডেকে বললেন, "আমি একজন নারীকে জানি, যার কোন সম্পদ নেই, বয়স্ক এবং সাথে একটা ইয়াতিম সন্তান আছে কিন্তু তিনি জান্নাতি, তোমাদের মধ্যে কেউ কি একজন জান্নাতি নারীকে বিয়ে করতে চাও?" এইকথা শুনে জায়েদ ইবনে হারিসা (রাঃ) নবীজির কাছে এসে বিয়ের প্রস্তাব দিলেন I নবীজি উম্মে আইমানের সাথে কথা বলে বিয়ের আয়োজন করলেন I বিয়ের দিন রাসূল (সাঃ) জায়েদকে বুকে জড়িয়ে আনন্দে ও ভালোবাসায়, ভেজা চোখে, কান্না জড়িত কণ্ঠে বললেন,  "তুমি কাকে বিয়ে করেছো, জানো জায়েদ ?" -হাঁ, উম্মে আইমানকে I জায়েদের উত্তর I নবীজি বললেন, -"না, তুমি বিয়ে করেছো, আমার মা কে "

সাহাবীরা বলতেন, রাসূল (সাঃ) কে খাওয়া নিয়ে কখনো জোর করা যেত না I উনি সেটা পছন্দ করতেন না I কিন্তু উম্মে আইমান একমাত্র নারী, যিনি রাসূল (সাঃ) কে খাবার দিয়ে "খাও".." খাও".. বলে তাড়া দিতেন I আর খাওয়া শেষ না হওয়া পর্যন্ত পাশে বসে থাকতেন I নবীজি মৃদু হেসে, চুপ চাপ খেয়ে নিতেন I রাসূল (সাঃ) উনার দুধ মাতা হালিমাকে দেখলে যেমন করে নিজের গায়ের চাদর খুলে বিছিয়ে তার উপর হালিমাকে বসতে দিতেন ঠিক তেমনি মদিনায় হিজরতের পর দীর্ঘ যাত্রা শেষে উম্মে আইমান যখন ক্লান্ত হয়ে পড়েছিলেন নবীজি উনার গায়ের চাদরের একটা অংশ পানিতে ভিজিয়ে, উম্মে আইমানের মুখের ঘাম ও ধুলোবালি নিজ হাতে মুছে দিয়েছিলেন এবং বলেছিলেন, "উম্মি ! জান্নাতে আপনার এইরকম কোন কষ্ট হবে না" । নবীজি মৃত্যুর আগে সাহাবীদের অনেক কিছুই বলে গিয়েছিলেন I সেই সব কথার মধ্যে একটা ছিল উম্মে আইমানের কথা I  বলেছেন, "তোমরা উম্মে আইমানের যত্ন নিবে, তিনি আমার মায়ের মত I তিনিই একমাত্র নারী, যিনি আমাকে জন্ম থেকে শেষ পর্যন্ত দেখেছেন I আমার পরিবারের একমাত্র সদস্য, যিনি সারাজীবন আমার পাশে ছিলেন I" সাহাবীরা সেই কথা রেখেছিলেন I গায়ের রং নয়, এক সময়ের কোন ক্রিতদাসী নয়, তাঁর পরিচয় তিনি যে নবীর আরেক মা I মায়ের মতোই তাঁরা, এই বৃদ্ধা নারীকে ভালোবেসে আগলে রেখেছিলেন I

Source: Collected

রাসূলের সাহাবি আব্দুল্লাহ ইবনে মাসউদ

আব্দুল্লাহ ইবনে মাসউদ (রা.) ছিলেন নবিজির একনিষ্ঠ খাদেম। সফরে, গৃহের অভ্যন্তরে, বাইরে সব সময় তিনি তাঁর সঙ্গে থাকতেন। কোনো মজলিসে যাওয়ার সময় ইবনে মাসউদ নবিজি (সা.)-এর জুতা বগলদাবা দিতেন। নসিহত করার সময় নবিজি লাঠি তার হাতে দিতেন। নসিহত করে বের হলে তিনি জুতা সাজিয়ে দিতেন পরার জন্য। নবিজি একা বের হলে তিনি অস্ত্রে সজ্জিত হয়ে বের হতেন। (মুসনাদে আহমাদ)।

রাসূল (সা.) ঘুমালে তাঁকে ঘুম থেকে জাগিয়ে দিতেন, গোসলের সময় পর্দা দিতেন। মিসওয়াক বহন করতেন। তিনি যখন হুজরায় অবস্থান করতেন তখনো তার কাছে যাতায়াত করতেন। রাসূল (সা.) তাকে যখনই ইচ্ছা তাঁর কামরায় প্রবেশ এবং কোনো ধরনের দ্বিধা-দ্বন্দ্ব ও সংকোচ না করে তার সব বিষয় অবগত হওয়ার অনুমতি দিয়েছিলেন। এবং তার পারিবারিক আলোচনায় বসারও অনুমতি দিতেন। এ কারণে তাকে ‘সাহিবুস সির’ বলা হয়। (মুসনাদে আহমাদ)।

তার সঙ্গে মহানবি (সা.)-এর সম্পর্ক এতটাই দৃঢ় ছিল যে অনেকে তাকে মহানবি (সা.)-এর পরিবারের সদস্য ভাবতেন। তিনি ও তার মা প্রায়ই মহানবি (সা.)-এর বাড়ি যেতেন। হজরত আবু মুসা আশআরি (রা.) বলেন, আমরা মদিনায় এসে ইবনে মাসউদকে রাসূল (সা.)-এর পরিবারের সদস্য হিসাবেই মনে করতাম। কেননা রাসূল (সা.)-এর কাছে তার ও তার মায়ের অধিক পরিমাণে যাওয়া-আসা ছিল। (তিরমিজি, হাদিস : ৩৮০৬)।

নবিজির সান্নিধ্য লাভ করতে করতে তিনি এমন পর্যায়ে চলে গিয়েছিলেন যে তার আচার-আচরণ ও চলাফেরায় নবিজির প্রভাব পরিলক্ষিত হতো। হজরত হুজাইফা (রা.) বলেন, সাহাবায়ে কিরামের মধ্য থেকে চলাফেরা ও আচার-ব্যবহারে রাসূলুল্লাহ (সা.)-এর সঙ্গে সর্বাধিক সাদৃশ্যপূর্ণ ছিলেন আব্দুল্লাহ ইবনে মাসউদ। (তিরমিজি, হাদিস : ৩৮০৭)।

তাই সাহাবায়ে কিরামও তার প্রতি সুধারণা পোষণ করতেন। হজরত আলী (রা.) বলেন, যদি আমি কাউকে বিনা পরামর্শে আমির নিযুক্ত করি, তাহলে ইবনে মাসউদকে করব। (তিরমিজি, হাদিস : ৩৮০৮)। ইবনে মাসউদ খোদ রাসূল (সা.)-এর শিক্ষালয়ে শিক্ষালাভ করেন। তাই সাহাবিদের মধ্যে যারা কুরআনের সবচেয়ে ভালো পাঠক, তার ভাব ও অর্থের সবচেয়ে বেশি সমঝদার এবং আল্লাহর আইন ও বিধিবিধানের সবচেয়ে বেশি অভিজ্ঞ, তিনি ছিলেন তাদেরই একজন।

তিনি অত্যন্ত বিশুদ্ধ ভাষায় কুরআন তেলাওয়াত করতেন। তার কুরআন তেলাওয়াতের প্রশংসা করেছেন মহানবি (সা.)। হাদিস শরিফে ইরশাদ হয়েছে, রাসূলুল্লাহ (সা.) বলেন, যে ব্যক্তি কুরআন যেভাবে নাজিল হয়েছে সেভাবে পড়তে চায়, সে যেন ইবনে মাসউদের মতো পড়ে। (মুসনাদে আহমাদ)।


চোখের পানি কোনো সাধারন পানি নয়!

চোখের পানি নিয়ে উইলিয়াম ফ্রে নামে একজন বিজ্ঞানী প্রায় ১৫ বছর গবেষণা করেছেন। গবেষণা শেষে তিনি বলেছেনঃ "চোখের পানি কোনো সাধারণ কিছু নয়। এটি পানি, শ্লেষ্মা, তেল, ইলেক্ট্রোলাইট-এর এক জটিল মিশ্রণ।

*এটি ব্যাকটেরিয়া প্রতিরোধী, যা চোখকে ইনফেকশন থেকে রক্ষা করে। এটি কর্নিয়াকে মসৃণ করে, যা পরিষ্কার দৃষ্টির জন্য অত্যাবশ্যকীয়।

*এটি কর্নিয়াকে যথেষ্ট আর্দ্র রাখে এবং অক্সিজেন সরবরাহ দেয়।

*এটি চোখের জন্য ওয়াইপার হিসেবে কাজ করে, যা চোখকে ধুয়ে ধুলোবালি থেকে পরিষ্কার করে।"

চোখের পানি যদি শুধুই পানি হতো, তাহলে তা ঘর্ষণের কারণে চোখ শুকিয়ে জ্বালা পোড়া করত। শীতকালে তাপমাত্রা শূন্য ডিগ্রি হলে পানি শুকিয়ে জমে বরফ হয়ে যেত! আবার চোখের পানি যদি শুধুই এক ধরনের তেল হতো, তাহলে তা চোখের ধুলাবালি পরিষ্কার না করে উলটো আরও ঘোলা করে দিত।

চোখের পানির মধ্যে প্রকৃতির লক্ষ উপাদান থেকে এমন বিশেষ কিছু উপাদান ব্যবহার করা হয়েছে, যার এক বিশেষ মিশ্রণ একই সাথে পরিষ্কার, মসৃণ এবং জীবাণুমুক্ত করতে পারে এবং অক্সিজেন সরবরাহ করতে পারে। চোখের পানির এই ব্যাপারটা চিন্তা করলেই আল্লাহ্'র প্রতি কৃতজ্ঞতায় মস্তক অবনত হয়ে যায়।


এক চোখের পানিতেই আল্লাহ্ তায়ালা  কত-শত অনুগ্রহ দেখিয়েছেন, কত সুক্ষ্ম, কত পরিকল্পনা করে সৃষ্টি করেছেন! একটু উনিশ থেকে বিশ হলেই ঘ্যাচাং! ভাবনার মোড়কে আটকানো অসম্ভব!

فَبِأَىِّ ءَالَآءِ رَبِّكُمَا تُكَذِّبَانِ

"অতএব, তোমরা উভয়ে তোমাদের পালনকর্তার কোন কোন অনুগ্রহকে অস্বীকার করবে?"

|সূরাহ আর-রহমান,আয়াত-১৩|

Source: Collected

ChatGPT / 10 Ways You Can Use ChatGPT to Learn Better
« on: May 08, 2023, 10:09:18 AM »
10 Ways You Can Use ChatGPT to Learn Better

Strengths and Weaknesses of LLMs

Using applications like ChatGPT requires some care. Part of the difficulty is that ChatGPT’s human-like conversation abilities can be deceptive. Feeling like you’re talking to a real person encourages you to rely on conversational expectations that may not hold with a machine. For instance, we generally expect that most people do not make up facts. Large language models, however, routinely violate this expectation by providing fluent answers that may be totally wrong. The metacognitive ability to know what you don’t know is underdeveloped in these applications.

Another expectation we have is that verbal fluency tracks other aspects of intelligence. We expect that someone who can spout lines from Shakespeare, explain quantum computing, and give a proof of the prime number theorem in rhyming verse would also be able to count. Thus, naively treating LLMs like a really smart and knowledgeable person is likely to backfire.

Those caveats aside, ChatGPT is clearly helpful for a range of tasks. Simon Willison suggests thinking of LLMs as a “calculator for words”—something that can do useful things with text—rather than as a general-purpose intelligence or smart person.

I tend to agree. The more we can distinguish the cases where LLMs work well from where they don’t (yet), the more we’ll be able to take advantage of the new capabilities without falling into unexpected traps.

Ten Useful Learning Strategies with ChatGPT

After receiving dozens of emails from my audience on how they have been personally using ChatGPT to learn, I’ve compiled some tips with some of the most common suggestions.

1. Create your own Socratic tutor.

By far, the most common use readers reported was using an LLM as a personal tutor. Asking ChatGPT to explain tricky concepts, unfamiliar code or problems seems like an area where LLMs might do alright. And the only reasonable substitute (a human expert) is notoriously expensive and in short supply. If you do this in conjunction with a class or textbook, the risks of mistakes also seem attenuated since you still have a primary source to compare against. Challenge explanations that don’t jive with what you’ve read in the book rather than taking everything the AI says at face value.

2. Practice chatting in new languages.

The next most common way people used LLMs to learn better was as a language tutor. This seems like a task LLMs are well-equipped for. Whatever their other flaws, they can produce grammatically correct text. Many people set up their conversations with ChatGPT so that the AI could go back and forth between the language they are learning and English explanations when they got confused. Likely, those explanations may be imperfect, but human tutors also often give incorrect accounts of the grammar and vocabulary they manage to use proficiently.

Another use is rewriting texts to be at a more beginner-friendly level of reading comprehension. Graded readers and comprehensive input are great strategies for learning to read in another language. Unfortunately, learner materials are often sparse or uninteresting. You can use an LLM to transform a text you want to read that is written at a fluent native level into something appropriate for your current ability.

Duolingo seems to be getting in on the LLM game as well. I’ve been harsh on the drag-and-drop style of language learning used in earlier versions, but these new advances may force me to revise my opinion.

3. Generate summaries of longer texts.
Summaries are another area where LLMs seem to excel. Consumer applications already exist for generating summaries of journal articles or research topics. Several readers said they were using these AI tools to provide digests of their substantial reading material, helping them keep atop new developments in their field.

Good summaries, especially those fine-tuned to your particular needs, might be a good way of navigating the large information loads we often face in knowledge work. You could use it to help prioritize which documents to read in-depth or do a first pass organizing unfamiliar material.

4. Dialog with long documents.

LLMs also can help you “ask questions” of longer texts. For instance, when reading a scientific paper you could quickly query the sample size or ask for the methodology or results. Consensus does this while offering references, so the risk of mistakes seems reduced when you can easily double-check the LLM’s work. While there are more fanciful usages here, such as people asking ChatGPT to impersonate a given writer and dialog with them, I suspect the ability to ask natural-language questions of documents and receive replies with references is a useful tool for dealing with large texts. That said, you must be prepared to fact-check the LLM’s answers. For instance, in the dialog captured below, I asked ChatGPT to list evidence supporting strongly-guided instruction, and it cited a review article by Mayer. But it falsely claimed Mayer’s work was a meta-analysis, which it isn’t. In fact, the paper isn’t even a comprehensive literature review but simply looks at three prominent cases of the failure of discovery learning. If taken at face value, this response can potentially mislead, but it’s relatively easy to “check” the AI’s work if you know what text it is transforming.

5. Rewrite texts at different levels of explanatory depth.

A major difficulty in following expert thinking is that most expert-level text is written for other experts. Concepts are unexplained, context is lacking and jargon abounds. This means that most people must rely on translators, such as general-market nonfiction or science writers, who present what experts think in a more readable format. There seem to be two approaches to using AI tools here. One is simply asking an LLM to explain a popular concept in simpler terms, such as: “Explain quantum computing like I’m an eighth-grader.” The other is to provide ChatGPT with a text or explanation and ask the AI to rewrite it in a more digestible manner.

I tend to think the latter is a little more reliable since you have the source material to compare with rather than taking ChatGPT’s word for it.

6. Clear up unfamiliar jargon.

Several years ago, I remember reading Tyler Cowen’s Marginal Revolution blog and being perplexed by his frequent, unexplained use of the term “Straussian” to describe ideas or other thinkers. I Googled for an explanation, but none was forthcoming. After a lot of research, I understood the term as meaning, roughly, “closely reading between the lines in prominent thinkers’ ideas, looking for what they really meant but couldn’t always express because of prevailing censorship and intellectual orthodoxy.”

7. Create study plans and agendas.

This usage surprised me, but it showed up enough times among reader replies that I include it here. People seem to like using AI to tell them how and when to learn. For instance, some readers asked ChatGPT to break down a complex learning goal and give them a curriculum. Others preferred to go even further, asking for ChatGPT to create a studying schedule for them, given their constraints for the day. I probably wouldn’t trust LLMs to give me a well-designed curriculum for a subject. But if I was learning something completely new, it might be a decent starting point. Sometimes the hardest part of approaching a new field is breaking down what appears to be an insurmountable goal. Similarly, sometimes being told when to study can help overcome the inertia of getting started. While skill breakdowns might be alright, ChatGPT still struggles with creating reading lists, confabulating books and references. Thus, while it might do well for decomposing an ambiguous learning task, I wouldn’t trust it to give me good resources (yet).

8. Provide refreshers on forgotten or infrequently used tools.

Programmers were the biggest professional group to reply to my query. I can’t say whether this is because programming is uniquely well-suited to LLMs or because programmers, as a group, are more likely to adopt novel software tools. The productivity advantages for programmers seem obvious. I don’t write much code these days, so I haven’t made much use of this well-publicized feature of LLMs. But since a lot of coding is relatively routine, the ability to have a machine create the first draft for an algorithm clearly saves a lot of time. While there are cases of people with zero programming knowledge relying on AI output to build applications, I suspect these might be tricky to debug and maintain. In contrast, an expert programmer can override ChatGPT’s output for a language he or she knows particularly well. The place LLMs seem to work really well is at the fringes of a programmer’s expertise. Many programmers told me that they found AI helpful in getting starting hints in unfamiliar languages or tools. Their base of programming experience allowed them to make sense of and implement the output, but their unfamiliarity with the underlying language meant the AI saved them a lot of time.

9. Generate flashcards based on text. (Tentative)

Flashcards are a powerful learning tool. They’re also a pain in the butt to make. Some readers said they were using ChatGPT to generate flashcards for subjects they’re studying. This seems well within the LLM abilities as a “calculator for words.” Thus, with the correct prompts, you could get fairly good results here—provided you’re inputting the material you wish to see transformed into flashcards and not expecting the LLM to get the facts on its own (see below).

However, given the difficulty of making “good” flashcards, I wouldn’t enter any into my Anki without reviewing them first. Nonetheless, making flashcards is tedious, so getting a first draft that I later review might speed up the process considerably. The risks seem relatively limited if you confirm the cards’ correctness before putting them in your deck.

10. Use it to organize your notes. (Advanced)

As someone who does a lot of research, I often waste a lot of time trying to locate my notes. Robert Martin finds the same problem. Searching via keywords is fraught because sometimes you can’t remember the exact term you used, even if the meaning is roughly the same. Martin solves this problem by using the embedding feature of LLMs. While not strictly ChatGPT, this tool from the same family of natural language processing techniques allows you to find semantically-related notes rather than exact keyword matches. Personalized LLMs that live on your hard drive and access your existing data may be a valuable application. I’d love to be able to search things I know I’ve seen but can’t quite recall where.

Some Things NOT To Do

1. Don’t expect AI to get facts right.

LLMs frequently make stuff up. These hallucinations are problematic if you depend on ChatGPT to give correct answers. The prevalence of these mistakes is difficult to say right now. When Wikipedia was released, for instance, “experts” were in an uproar about how the user-generated nature of the website meant it couldn’t ever be relied upon as a source. Except Wikipedia actually does fairly well, and some of these knee-jerk reactions were misplaced. LLMs haven’t reached Wikipedia’s quality in terms of facts, and we still don’t know much about when they’re likely to get an answer right and when they’re likely to make stuff up. For now, it seems best to use them for situations where the cost of an incorrect answer is minimal, either because you can look it up in a verified source, or because your use of the AI for isn’t factual in nature.

2. Don’t expect AI to get citations right.

While LLMs sometimes mess up facts, they seem abysmal at getting citations right. They frequently invent authors, papers, studies and research. I wouldn’t use a LLM for any research that I needed to cite, and I would always double-check the sources it does provide. Similarly, I wouldn’t ask an LLM to give me a reading list or references to specific books or authors (unless, possibly, the authors were quite famous and likely to be well-represented in the data set).

3. Don’t expect AI to get the math right.

I believe it’s a mistake to attribute general intelligence to LLMs based on their ability to do many tasks at a human level or beyond. As with chess bots and image classifiers, the technology behind LLMs is extremely narrow compared to what we would expect of a human who scored similarly on verbal tests. One finding from psychology is that much of reasoning is performed by different subsystems in the brain than those devoted to language. This paper argues that LLMs seem to match the neurological evidence from double-dissociation studies: you can have fluent verbal abilities with seriously impaired reasoning and vice versa. As such, LLMs are really bad at math. And not just higher-level math that humans struggle with. LLMs often fail at basic counting tasks. Thus I suspect LLMs would be uniquely bad at a task like providing practice problems for a math class and grading the answers. ChatGPT might be able to explain a math concept well, but be unreliable at actually using it.


ভয়ংকররূপে আসছে কৃত্রিম বুদ্ধিমত্তা, গুগল ছেড়ে বললেন এআই ‘গডফাদার’

৭৫ বছর বয়সী হিনটন নিউ ইয়র্ক টাইমসকে এক বিবৃতিতে বলেছেন, আর্টিফিশিয়াল ইনটেলিজেন্সের উন্নয়নে তার যা কাজ, সে জন্য এখন তার অনুশোচনা হচ্ছে। সারা জীবন কাজ করেছেন কৃত্রিম মেধা (আর্টিফিশিয়াল ইন্টেলিজেন্স বা এআই) নিয়ে। পেয়েছেন একাধিক স্বীকৃতি ও পুরস্কার। কৃত্রিম বুদ্ধিমত্তা বা আর্টিফিশিয়াল ইনটেলিজেন্সের ‘গডফাদার’ হিসেবে সবাই তাকে চেনে। তবুও কৃত্রিম বুদ্ধিমত্তার অপকারিতা এবং ঝুঁকি নিয়ে নির্দ্বিধায় কথা বলার জন্য গুগল থেকে পদত্যাগ করেছেন হিন্টন। কৃত্রিম বুদ্ধিমত্তার কারণে ভবিষ্যতে কী ঘটতে পারে তা নিয়েই ভয় পাচ্ছেন তিনি।

২০১৮ সালে কৃত্রিম বুদ্ধিমত্তা নিয়ে যুগান্তকারী কাজের জন্য ‘ট্যুরিং অ্যাওয়ার্ড’ জিতেছেন। কিন্তু এখন তার দাবি, তিনি যে প্রযুক্তি নিয়ে কাজ করেছেন তার পরিণতি ভয়ংকর। বিবিসিকে তিনি বলেছেন, এআই চ্যাটবটগুলো এখন এমন বিপজ্জনক মাত্রায় বুদ্ধিমান হয়ে উঠেছে, যা রীতিমতো আতঙ্ক জাগানোর মতো। এখনো তারা আমাদের চেয়ে বেশি বুদ্ধিমান হয়ে ওঠেনি। কিন্তু আমার মনে হয়, শিগগিরই তারা আমাদের ছাড়িয়ে যাবে। 

সংবাদমাধ্যম ‘দ্য নিউ ইয়র্ক টাইমস’-এর সঙ্গে এক সাক্ষাৎকারে হিন্টন জানিয়েছেন, কৃত্রিম বুদ্ধিমত্তার অপব্যবহার করছে সমাজের একাংশ। ভুয়া ছবি এবং খবর তৈরিতে যেভাবে এআই ব্যবহার করা হচ্ছে তা নিয়েও উদ্বেগ প্রকাশ করেছেন হিন্টন। তিনি জানান, এআই শিল্পে প্রতিযোগিতা বেড়ে যাওয়ার কারণে সবাই নতুন নতুন কৃত্রিম বুদ্ধিমত্তা নিয়ে কাজ করছেন। ফলে এর অপব্যবহারকে ঠেকানো অসম্ভব হয়ে উঠছে।

ব্রিটিশ-কানাডিয়ান কগনিটিভ সাইকোলজিস্ট ও কম্পিউটার বিজ্ঞানী জেফ্রি হিনটন এখন মনে করছেন, মানুষের মস্তিষ্ক যতটা তথ্য ধারণ করতে পারে, শিগগিরই তাকে ছাড়িয়ে যাবে চ্যাটবট। ফলে বিশ্বব্যাপী ধীরে ধীরে বিভিন্ন সংস্থায় কর্মী ছাঁটাই বাড়তে পারে। চাকরির অভাব দেখা দিতে পারে। কৃত্রিম মেধা বিশ্বকে এমন একটা জায়গায় নিয়ে যাচ্ছে, যেখানে কোনটা ‘সত্য’ আর কোনটা ‘মিথ্যা’ তা খুঁজে বের করা ধীরে ধীরে কঠিন হয়ে পড়বে।

ব্রিটিশ-কানাডিয়ান কগনিটিভ সাইকোলজিস্ট ও কম্পিউটার বিজ্ঞানী জেফ্রি হিনটন এক দশক আগে তথ্য-প্রযুক্তি সংস্থা গুগলে যোগ দিয়েছিলেন। তিনি কেন এত দিন পরে গুগল ছাড়লেন সে সম্পর্কে কিছু বলেননি। তবে তিনি টুইটারে টুইট করে জানান, ‘আমি গুগল ছাড়লাম এ জন্য, যাতে কৃত্রিম বুদ্ধিমত্তা নিয়ে তৈরি হতে চলা সংকটজনক পরিস্থিতি নিয়ে নির্দ্বিধায় কথা বলতে পারি। এর প্রভাব যেন গুগলে না পড়ে, তাই আমি সংস্থা থেকে পদত্যাগ করেছি। তবে আমাকে স্বীকার করতেই হবে, এআই ব্যবহারের ক্ষেত্রে গুগল অত্যন্ত দায়িত্বশীলভাবে কাজ করেছে।’

নিউ ইয়র্ক টাইমসের নিবন্ধে হিনটন সেইসব ‘দুষ্ট লোকের’ বিষয়েও সতর্ক করেছেন, যারা খারাপ কাজে এআই ব্যবহার করতে পরে। ব্যাখ্যা করে বিবিসিকে তিনি বলেন, পরিস্থিতি যদি সবচেয়ে খারাপ হয়, তখন এমনটা হতে পারে। মনে করুন, (রাশিয়ার প্রেসিডেন্ট ভ্লাদিমির) পুতিনের মতো বাজে লোকদের কেউ রোবটদের নিজস্ব লক্ষ্য ঠিক করার ক্ষমতা দিয়ে দিল। শেষ পর্যন্ত সেই নিজস্ব লক্ষ্য হয়ে দাঁড়াবে এ রকম– ‘আমার আরো ক্ষমতা চাই।’

যেরকম কৃত্রিম বুদ্ধিমত্তা আমরা তৈরি করছি, তা ধরনের দিক দিয়ে আমাদের বুদ্ধিমত্তার চেয়ে অনেকটাই আলাদা। তিনি আরো বুঝিয়ে বলেন, ধরুন আপনার দলে ১০ হাজার লোক আছে, তাদের মধ্যে কেউ একজন যখন নতুন কিছু শিখছে, স্বয়ংক্রিয়ভাবে দলের বাকি সবাই সেটা শিখে ফেলছে। আর এভাবেই এ চ্যাটবটগুলো যেকোনো মানুষের চেয়ে এত বেশি জানতে পারছে।

এ বিষয়ে গুগলের প্রধান বিজ্ঞানী জেফ ডিন এক বিবৃতিতে বলেছেন, ‘এআই-এর দায়িত্বশীল ব্যবহারের বিষয়ে আমরা অঙ্গীকারবদ্ধ। কী ধরনের ঝুঁকি তৈরি হতে পারে, সে বিষয়ে আমরা প্রতিনিয়ত শিখছি, সেই সঙ্গে আমরা উদ্ভাবনও চালিয়ে যাচ্ছি।’


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