What questions do you have about A.I. that you're too embarrassed to ask?

@claytonwalker That's a great question! Personally I think AI is a buzzword that's gonna fade eventually. I imagine it will be abstracted to the point where people don't really care or realize it's "AI". Instagram, TikTok, and FB recommendation algorithms are great examples of this

@claytonwalker I love this topic. First of all, a lot of AI builders will tell you we're not as far along as doom & gloom articles will have you believe. We still have to figure out really big issues in AI like context and emotional intelligence. I.e. People don't realize how complex we are and hard to replace! The A.I. is getting better and better but these are big problems to solve. I think an article on our psychological perception of AI and AI marketing is relevant, but also on an article by article basis I hope to separate fact from fiction and give people reasonable tips for how to succeed with AI.

@claytonwalker @yukioyama Absolutely! AI is becoming integrated into our daily lives without us even realizing it. It's amazing how technology is evolving. You're doing great work! 👍

@claytonwalker This is always an interesting topic to talk about. On the contrary, I just met one of the founders who is working AI creative designer set to reduce the number of designers in the creative team with AI supporting creating static creatives for them. Starting with this, they want to love to video and what not.

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@dima_isakov this is a very valid point - it does make it easier to copy someones style. But where do we draw the line on this? It happens all the time in design already - all artists are inspired by other artists whether they realize it or not. Does this come down to an ethics issue of whether or not you credit the original artist? Recently Sarah Bahbah accused Selena Gomez’s team of out right stealing her ideas when shooting at the same location. Everyone has a different argument for where the line should be. we do not have the best system in place to protect individuals creations and AI definitely makes this easier to circumnavigate. I’m interested to see how laws change to adapt to the advancements in technology and protecting artists.

I also agreed.

@dima_isakov @claytonwalker Absolutely, it's a complex issue. Giving credit to original artists is crucial. We need better protections for creators in the age of AI. 🎨🤔

@dima_isakov I've been working as a professional concept artist in film and TV for 25 years and can definitely say my life has heavily been affected by AI. I have large collections of artwork out there that have been scraped for AI I'm sure. My opinion, which I feel will be met with the blunt end of a social witch hunt is; Why not? Nothing is completely original. Should we talk about Warhol and any number of creators who simply take the work of those before them and reinvent it, we need to get over this idea of originality; it doesn't exist. In the end this is just an extension of what we've been doing for centuries; the human mind is trained by experiences that inform design / art choices, where's the outcries? Did Greg Rutkowski really come up with the original concept of a dragon? yet he and many others seem very concerned with their artwork been used to train AI systems. Why? these individuals did the same process in training their own imagination, they saw the works of those before them, ie a dragon, became inspired and created something new which can be interpreted as original. This is acceptable correct? so why should an artificial system be denied the same process of learning and producing originality? Its a selfish argument to say another human artist can learn from my artwork and apply it to their own original creations, but an artificial system cannot. So for me, as an concept artist and content creator, i'm more than happy for AI systems to use my work to train their data sets so others can use it to make original content. Obviously getting paid for this is a positive thing ;) And yes, i do actually get paid for my work been used to train data sets, but even if I didn't my opinion would be the same :)

@claytonwalker Yeah. This is a very complex issue that needs improvement for a long time. And it's not just AI, copyrights have been infringed before. But as you said, it's even easier now. I think if authors whose style is copied were compensated monetarily for each copy, it would make copying a bit more fair. There are other ways, but this one seems like the first.

@carterparks I like this topic! I think it would be interesting to hear how answers might differ from product people to customer support to A.I. engineers.

@carterparks I come with the perspective as a professional artist, so this question is a frequent point of discussion for me. The way i see it; the question is; do you care if it has a human touch? for example, you go to an art gallery and see a piece of art, do you care if it was created by a human? perhaps, because we feel a human connection. When you pick up a package of cornflakes or fruit loops do you really care if the artwork has been touched by a human? we're surrounded every day by artwork, from simple package designs to cars, clothing etc, how much do we really care about the human touch? or just that it visually looks appealing? Here's the thing about AI, while the concept is definitely abstract, it really understands by brute force, what visually works and looks appealing, so if thats the goal, then why not offset that to an automated system where speed and cost are more important than value? Design and art are two different things, design has a purpose, to generate money, art has a purpose; to express an idea or story. So how do you decide human over API? well, you just simply decide whats more important to you :)

@carterparks taxes 😂

@carterparks Great question, Carter! The line between tasks suitable for automation and those requiring a human touch often depends on the complexity and nuance of the task, as well as the potential for personal interaction and empathy. 1. Repetitive and Data-Driven Tasks: Tasks that are repetitive, data-driven, and rules-based are prime candidates for automation via APIs. These include data entry, basic customer queries, scheduling, and analytics. Automation here can save time and reduce errors. 2. Creative and Strategic Tasks: On the other hand, tasks that involve creativity, complex problem-solving, strategic decision-making, and personal interaction generally benefit from a human touch. These include content creation, strategic planning, and personalized customer support. 3. Hybrid Approach: Often, a hybrid approach works best. For example, in our work at StockLibrary.ai, we use AI to generate custom stock photos based on user inputs, but the final curation and creative direction involve human judgment. This blend of automation and human insight ensures both efficiency and quality. 4. Context Matters: The specific context and industry also play a significant role. For instance, in healthcare, automated systems can handle appointment scheduling and reminders, but diagnosis and patient care require human expertise and empathy. I’m curious to hear how others, especially those in different roles like product management, customer support, and AI engineering, navigate this balance. And @claytonwalker , automating taxes would indeed be a dream come true! 😂

@carterparks The line between tasks appropriate for automation via API and those needing a human touch can be drawn based on: Repetitiveness: Automate repetitive, rule-based tasks (e.g., data entry). Complexity and Nuance: Tasks requiring human judgment, creativity, and emotional intelligence should remain human-led (e.g., creative writing, complex decision-making). Quality and Context: Automate where consistency and speed are crucial, but retain human intervention where context and adaptability are essential (e.g., customer support). In summary, automate repetitive and rule-based tasks, and reserve tasks requiring judgment, creativity, and emotional intelligence for humans.

@boris_moris44 This one here is a great place to start https://www.coursera.org/learn/a...

@boris_moris44 @koltsov We are launching ChandlerAi 🙏.

@david_bowman1 can you provide more info on ChandlerAI?

@sugar_free_app We are launching ChandlerAi.

@harsha_01 wish you good luck. Will share your link tomorrow to my linkedin. I will support.

@weiyuyang We are launching ChandlerAi 🙏.

@weiyuyang Hi Weiyu, That's a really interesting point you’ve brought up. AI’s potential to bring about equality is a complex issue. On one hand, AI can democratize access to powerful tools and resources that were previously only available to those with significant resources or expertise. This can help level the playing field in many ways. However, you’re right that simply having access to AI tools doesn’t automatically translate to generating valuable output. Original ideas and creativity are still crucial. AI can amplify and enhance these ideas, but it can’t replace the unique human spark that drives innovation. One way to look at it is that AI can be a great equalizer when it comes to access and efficiency. For example, at StockLibrary.ai, we provide users with the ability to generate high-quality custom stock photos. This gives everyone—from small business owners to large enterprises—access to professional-grade images without needing extensive resources. But you're correct that there’s a risk of widening the gap if AI tools are not used effectively. Education and support are key. By helping users understand how to best leverage AI tools and encouraging a culture of continuous learning and creativity, we can work towards narrowing this gap. In the end, AI is a tool that, when used thoughtfully and creatively, can empower individuals and bridge gaps. It’s about finding the right balance and ensuring that everyone has the opportunity to learn and grow with these new technologies. What are your thoughts on ways we could better support users to maximize the benefits of AI?

@rockzhang For people who don't care about AI, they might miss out on tools that can simplify tasks and boost productivity. They could find it harder to stay competitive in fields that increasingly rely on AI. However, it's perfectly fine to focus on areas that don't depend heavily on AI. Staying open to learning about new technologies, though, can be beneficial as the world continues to evolve.

@abdellah_abbous Yesss love this. Questions like this can help us understand what AI is actually capable of today, and what it could be capable of in the future.

@abdellah_abbous Haha that's good one!

@konrad_sx We are launching ChandlerAi 🙏.

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@zijian That's actually a great question. One of my buddies who works at OpenAI gave me an extremely simplified version of how the algorithm works. The algorithm is pretty simple, the input = 8 words, and the output = the next 8 predicted words. So you just feed it enough text until it learns how to predict output from given input.

@zijian this is templates

@zijian that's a good question

@ryan_motiff We are launching ChandlerAi 🙏.

@josej30 legitimately curious why AI models hallucinate as well. seems to happen when u give it long questions. i guess some people do that too

@josej30 Ty! This is going on the list. And we're working on some articles now about how hallucinations are being addressed (and how even those fixes are falling short). But I, for one, can definitely better understand why hallucinations happen at all. And on the emath!

@josej30 Interesting question that requires a complex answer. I'll try to explain it simply. Math Underneath LLMs LLMs like GPT use deep learning, specifically transformers, involving: - Vectors and Embeddings: Words are converted into numerical arrays to capture semantic relationships. - Matrix Multiplications: Transform input vectors into hidden states and outputs. - Attention Mechanism: Computes weighted sums of inputs to focus on different parts. Vector Operations -Dot Product: Measures similarity between vectors. -Addition/Subtraction: Captures semantic relationships. -Normalization: Ensures vectors have unit length. AI Model Hallucinations Hallucinations happen due to: - Overgeneralization: Generating text based on learned but inapplicable patterns. - Lack of Context: Insufficient information leads to guesses. Training Data: Errors or biases in data are reproduced.

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@thankyousir Love this. I think this will be difficult and vague to do in a single article, but we will try to approach this viewpoint in every newsletter - what can it actually do in each circumstance, and what's fiction or far off.

@ryan_motiff again, AI comment much?

@vitor_seabra Oo great question.

@vitor_seabra Hi Vitor, Great question! It’s true that data science and machine learning require skilled professionals, which can be expensive. I think there might be several reasons why AI startups are emerging despite these costs: Open-Source Tools: Tools like TensorFlow and PyTorch are invaluable. They provide a robust foundation for AI development and are constantly updated, allowing startups to build on strong, existing frameworks without starting from scratch. Cloud Services: Platforms like AWS, Google Cloud, and Azure offer scalable infrastructure on a pay-as-you-go basis. This accessibility means startups can experiment and deploy solutions without massive upfront investments. Pre-trained Models: The availability of pre-trained models is a huge advantage. Startups can leverage existing models and focus on customizing them for their needs, which saves both time and resources. Funding and Investment: Although the funding landscape can fluctuate, AI remains a hot area for investment. Many startups still manage to secure funding, especially if they present strong, innovative solutions. Collaboration and Outsourcing: Partnering with academic institutions or outsourcing specific tasks allows startups to access top talent and expertise while managing costs effectively. While these factors contribute significantly to the rise of AI startups, it's also worth noting a few challenges: Competition: As the AI field matures, competition among startups increases. Having a strong value proposition and a well-defined niche is crucial to stand out. Regulation: Evolving regulations around data privacy and AI ethics could impact how startups develop and deploy their solutions. At StockLibrary.ai, we’ve tried leveraging some of these strategies to bring our AI-generated stock photo service to life efficiently. It’s about being resourceful and making the most of the tools and support available. What are your thoughts on these points? Have you noticed any other trends or strategies that AI startups are using?

@novicto_herlistianto thanks for enlightening this topic! amazing thoughts

@iamjasonlevin I tried it. I liked it. :)

@li_haha 😂

@bryantchen upvoted

@bryantchen Totally agree with you. ChatGPT has definitely made it super easy and comfortable to explore any question that comes to mind. It’s like having a chat with a friend who knows almost everything! 😄 How has it been helping you out the most?

@bryantchen @julie_su Hi Bryant and Julie, I couldn't agree more! Since ChatGPT came along, it feels like there's no such thing as a 'silly' question anymore. It's amazing to have a resource where you can ask anything without feeling embarrassed. It really is like chatting with a knowledgeable friend who’s always there to help out. 😄 For me, ChatGPT has been a game-changer, especially in brainstorming ideas and getting quick answers to technical questions. It’s incredible how it can provide insights and suggestions almost instantly. How about you, Bryant? What are some of the ways ChatGPT has been most helpful for you?