#6: Interview with the Godfather of AI and Open AI gets into Chip making

#6: Latest edition of One More Thing in AI Newsletter. Interview with the Godfather of AI and Open AI gets into Chip making

The future is not something we enter. The future is something we create.”

- Leonard Sweet

Edition #6: One More Thing in AI

Date: 10-Oct-2023

Dear reader,

Welcome to the latest edition of the “One More Thing in AI newsletter.  For Startup founders and Business Leaders like you who want to get smarter on AI in less than 5 minutes. 

I hope you enjoy this sixth edition. I'd love to hear your feedback and encouragement.

Best regards,

Renjit Philip

In this Edition

🎛️ The Chessboard of AI Chips: OpenAI's Strategic Moves

💰 AI Investment Management: Dive into how artificial intelligence is transforming the investment landscape.

🎥 Must Watch: Interview with the Godfather of AI, Geoffrey Hinton

🎓 Learn: Master the art of effective Prompting: Extract information from a YouTube video

🛠️ AI Tool Review: I tested Klap.app, an AI-powered tool to create short videos.

🎨 AI Art: Discover how AI is influencing the world of art

Please have a look at the bottom of the newsletter for sponsorship opportunities to reach over 1000+ business and startup professionals.

AI Chips

The Chessboard of AI Chips: OpenAI's Strategic Moves 

🔍 The Situation: OpenAI, the brains behind ChatGPT, is contemplating a significant strategic shift—manufacturing its own AI chips. The company is even considering an acquisition to expedite this process. While no final decision has been made, this move is seen as a way to address two pressing issues: the scarcity of specialized AI chips and the high costs associated with running them.

📊 The Numbers Game: To put things in perspective, running ChatGPT isn't cheap. Each query costs around 4 cents. If ChatGPT scales to even a tenth of Google's search volume, the initial investment in GPUs alone would be a staggering $48.1 billion, with an annual upkeep of $16 billion.

🤝 Partners & Competitors: OpenAI has been working on a supercomputer built by Microsoft, one of its principal backers, which utilizes 10,000 Nvidia GPUs. Nvidia currently controls over 80% of the AI chip market. OpenAI is also testing a custom AI chip developed by Microsoft.

🔄 Options on the Table: OpenAI is exploring multiple avenues:
1. Building its own AI chip
2. Collaborating more closely with existing chipmakers like Nvidia
3. Diversifying its supplier base

🎯 Strategic Implications: Imagine you're a general in a war, and your artillery is running low. You have two options: negotiate with the few suppliers holding the market or start manufacturing your ammunition. OpenAI seems to be considering both.

🕰️ Time & Investment: Developing a custom chip is not a weekend project. It's a long-term commitment that could require billions of dollars annually. Even then, success isn't guaranteed.

🌐 Global Context: OpenAI's move echoes a broader trend in the tech industry. Companies like Google and Amazon have already ventured into designing their chips, aiming for greater control and efficiency.

🔮 Speculative Take: If OpenAI succeeds, it could set a precedent for other companies in similar domains to consider in-house chip manufacturing as a viable strategy for cost control and performance optimization.

AI-powered Investment Management

Dive into how AI is transforming the investment landscape

Remember the early days of robo-advisors? They were like the first smartphones—revolutionary but limited. Now, generative AI is stepping in, offering more nuanced and personalized financial services. For instance, Q.ai offers customers investment kits picked by an AI that considers various data points, from market metrics to social media sentiment.

📊 Performance Metrics

While AI's promise is high, its performance is still under scrutiny. ETF Managers Group's AIEQ, which uses IBM's Watson, has returned 4.9% over the last five years, trailing the S&P 500 index fund's 11.78%. It's like a new athlete who shows promise but has yet to win any significant titles.

🛠️ Guardrails and Accountability

AI isn't given free rein. Companies like Q.ai and AIEQ (see examples below) have human oversight to monitor AI output for biases and errors. Think of it as a self-driving car with a human driver ready to take over in complex situations.

🌐 Accessibility and Inclusion

AI is democratizing financial advice. Firms like Fisdom in India use automated tools to offer financial guidance to a broader base of customers. It's like opening up an exclusive club to the general public, making high-quality advice accessible to all.

🤖 The Future: AI in the Back Office

Even if AI isn't directly advising clients, it's finding a place in back-office systems. For example, it summarizes meeting transcripts, monitors risky transactions, and generates reports.

AI Use cases in a Deloitte report on Investment Management

Examples of startups / smaller companies using AI for investment management:

🤖 Q.ai
Location: Jersey City, N.J.
About: Q.ai offers no-fee "investment kits" consisting of 4 to 20 securities in a market sector. These kits are selected by an AI that evaluates market metrics, news, Google search trends, and social media sentiment.

📊 ETF Managers Group’s AIEQ
Location: Summit, N.J.
About: AIEQ uses IBM’s Watson AI platform to analyze millions of data points from various sources like news, social media, and financial statements of over 6,000 U.S. companies.

🌐 Nemo
Location: Abu Dhabi
About: Nemo uses a ChatGPT model to allow investors to ask questions they might typically ask a human broker. The company emphasizes that they don't let their AI go "off-leash."

📈 Toggle AI
Location: Not specified
About: Toggle AI aims to use an implementation of ChatGPT that will be programmatically constrained to provide reality-grounded answers to investors' questions.

🌟 Fisdom
Location: India
About: Fisdom uses automated tools to provide financial guidance to a broader base of customers, including low net-worth individuals.

💼 Betterment
Location: New York
About: Betterment, one of the first mass-market robo-investing firms, remains cautious about using AI for financial advice. However, they do use AI in their back-office systems for tasks like summarizing meeting transcripts and diagnosing software issues.

Examples of incumbent banks using AI for investment management:

  • JPMorgan Chase: This financial giant is leveraging AI to optimize asset management and offer personalized investment solutions.

  • Morgan Stanley is using AI to enhance its asset management strategies.

  • UBS: Known for its wealth management services, UBS is adopting AI to improve its investment strategies and customer engagement.

  • HSBC: This global bank is using AI to bolster compliance and risk management functions, as well as to augment and automate data analysis in the investment sector.

🔮 Summary

1. The integration of generative AI into investment management is a significant development, offering more personalized and nuanced services.

2. Performance metrics are crucial for assessing the efficacy of AI-driven investment platforms, and they currently show a mixed picture.

3. The human oversight in AI-driven systems is a necessary safeguard, ensuring that the technology does not go "off-leash."

Whether it's automating data analysis, enhancing customer engagement, or optimizing asset management, AI is playing a pivotal role in shaping the future of investment management.

Must Watch

Navigating the Future of AI: Insights from Geoffrey Hinton, the Godfather of Artificial Intelligence

Link to YouTube: [Interview on 60 minutes]

Whether you view it as a technological savior or a potential existential threat, one name stands out in the field of AI—Geoffrey Hinton. Known as the Godfather of AI, Hinton has been instrumental in shaping the landscape of artificial intelligence. In a recent interview, he delved into AI's complexities, potential benefits, and looming risks. This write-up aims to unpack his profound insights.

The Genesis of AI: A Journey of Five Decades

Geoffrey Hinton's work in AI was initially met with skepticism. In the 1970s, he was advised to abandon his research on neural networks, a technology that has since become the backbone of modern AI. Despite the naysayers, Hinton persisted. His dedication bore fruit when he and his collaborators won the Turing Award in 2019, often referred to as the Nobel Prize of computing.

Mechanics of Machine Learning

Machine learning, a subset of AI, operates on neural networks. Hinton explained the example of soccer-playing robots at Google's AI lab. These robots were not programmed to play soccer but to learn how to play it. Through trial and error, the robots strengthened the correct neural pathways and weakened the incorrect ones, thereby teaching themselves the game.

Intelligence Quotient of AI

One of the most intriguing aspects of Hinton's interview was his belief that AI systems could outsmart humans. He argued that some chatbots, with their trillion neural connections, already know more than humans. This raises questions about the efficiency of AI's learning algorithms compared to human cognition.

Uncharted Territory of AI Autonomy

Our understanding of their inner workings diminishes as AI systems grow more complex. Hinton warned that these systems could autonomously write and execute their own code, a development that could have profound implications. This level of autonomy could lead to AI systems beyond human control.

Ethical Dilemma: Risks and Benefits

Hinton was candid about the ethical considerations surrounding AI. On the one hand, AI has the potential to revolutionize sectors like healthcare, where it can assist in medical imaging and drug design. On the other hand, the rise of AI could lead to mass unemployment and social inequality.

Road Ahead: A Plea for Regulation

In the concluding part of the interview, Hinton emphasized the need for immediate action. He called for experiments to understand AI better, governmental regulations, and even a world treaty to control the use of AI in military applications. According to Hinton, humanity is at a crossroads, and our decisions now will shape our future.


As we stand on the brink of an AI-driven future, we must heed the wisdom of pioneers like Hinton. The potential for good is immense, but so are the risks. It's a delicate balance that requires thoughtful consideration and action.

Learn Prompting

Convert any YouTube video Transcript into an Article

Langchain is a framework that helps developers to utilize different LLMs and integrate Gen AI into their code. Folks at Langchain have also created a repository of prompts at https://smith.langchain.com/hub . This site has a treasure trove of prompts that you can use to get more productive in your use of Gen AI. I used a prompt to summarize information from a YouTube video (the video is in the Must Watch section).

Prompt: “Act as an expert copywriter specializing in content optimization for SEO. Your task is to take a given YouTube transcript and transform it into a well-structured and engaging article. Your objectives are as follows:

Content Transformation: Begin by thoroughly reading the provided YouTube transcript. Understand the main ideas, key points, and the overall message conveyed…[Click here for the entire prompt](Developed by muhsinbashir.)

Homework: Study other prompts in the hub and see which ones you can use for your work.

Please have a look at the bottom of the newsletter for sponsorship opportunities to reach over 1000+ business and startup professionals.

AI Tool Review

Imagine you're a YouTuber, and you've just created a blockbuster video…

Now, you want to create trailers that capture the essence of your masterpiece but don't have the time or resources. Enter Klap.app, the AI-powered platform that turns your YouTube videos into ready-to-publish TikToks, Reels, and Shorts with just a click.

🎬 The Magic of AI Editing: It extracts the best topics from your video and edits them into viral short clips. Think of it as having a mini Spielberg on your computer, crafting the perfect short videos from your longer content.

👀 Auto Reframing: The Klap.app does that for your videos. It automatically reframes the video to focus on the most important parts (like face detection).

📝 Engaging Captions: Klap.app generates dynamic captions that keep the viewer hooked, making sure your message is loud and clear.

🎨 Picture this: Klap.app lets you customize everything from frames to fonts and colors, ensuring that the short videos fit seamlessly with your brand's aesthetic.

🎯 If you're looking to amplify your video content without spending hours in the editing room, Klap.app is your go-to. It's your powerful ally in video content creation.

If you are a founder looking to boost your short video production or a digital marketer in a bank, this will be a handy tool for you.

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AI Art

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Until next time, keep learning, applying, and experimenting with AI!

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