🎖️Godfather of AI wins Nobel Prize

Geoffrey Hinton, notable as an AI doomerism proponent, just won a Nobel Prize in Physics for he and his colleague John Hopfield's foundational work in machine learning and artificial neural networks.

Author

Jack Lajoie
October 08, 2024 • read time ~ 10 minutes

The Daily Current ⚡️

Shortly after California Governor' Gavin Newsom’s veto of the purported AI Safety Bill, the Nobel Prize in Physics went to a man widely regarded as “the Godfather of AI”, who says he deeply fears the technology he helped to create.

Maybe the Nobel Foundation is trying to tell us something 🤔 ? That, and much more in today’s Daily Current ↘️

 🔌 Plug Into These Headlines:

  1. “Godfather of AI” Geoffrey Hinton wins Nobel Prize in Physics

  2. Deloitte finds only 2% of boards reported being highly knowledgeable and experienced in AI

  3. Anticipating the Bubble Burst: Three AI Stocks poised for a plunge

  4. Amazon’s AI “Culture Coach”

  5. Rabbit (sort) of finally gave us the R1 feature they promised

Geoffrey Hinton, often referred to as the "Godfather of AI," was awarded the 2024 Nobel Prize in Physics alongside John Hopfield for their foundational work in machine learning and artificial neural networks.

  • Foundational Discoveries: Hinton's work laid the groundwork for many contemporary AI systems, making his discoveries crucial for ongoing research and development in machine learning.

  • Innovative Techniques: He has developed several critical techniques in neural network research, including:

    • Boltzmann Machines: A type of stochastic recurrent neural network.

    • Deep Belief Networks: A generative model that can learn to represent data hierarchically.

    • Capsule Networks: Introduced as a way to improve the performance of neural networks in recognizing patterns

  • Hinton's research primarily focuses on artificial neural networks, particularly deep learning, which has become the backbone of modern AI systems.

  • His work on the backpropagation algorithm in 1986 revolutionized how neural networks are trained, allowing for more efficient learning processes in multi-layer networks

Hinton is known for his “doomerism” attitude towards AI (the idea that it is capable of bringing about catastrophic events for humanity) and his credibility in the field helped lend legitimacy to the position, which was once considered a little crazy.

“I have suddenly switched my views on whether these things are going to be more intelligent than us, I think they’re very close to it now and they will be much more intelligent than us in the future. How do we survive that?”

Geoffrey Hinton

Ciodive.com did a great brief on this juicy little stat here. Furthermore, enthusiasm for AI adoption within these enterprise sectors has been fading. As we all navigate this process of figuring out exactly what AI is useful for, there have been plenty of hype trains derailed, and despite AI’s historically rapid adoption, stats like this help clarify who is really driving that adoption.

  • The report is part of an ongoing quarterly series by the Deloitte AI Institute to track Generative AI adoption trends, impacts, and challenges throughout 2024.

  • The Q3 survey was conducted between May and June 2024 and involved 2,770 AI-savvy business and technology leaders across 14 countries and six industries.

  • Lara Abrash, chair of Deloitte US, emphasizes the need for organizations to "govern at scale."

    • This involves challenging traditional boardroom approaches and implementing balanced processes to ensure that board time is focused on the most significant and strategic AI-related topics.

You can find the full Q3 “State of Generative AI in The Enterprise” report from Deloitte here.

We know we are in a bubble…right? Here are three AI-dependent stocks that have seen meteoric rises during this AI boom and could face a sharp reality check, with analysts predicting potential drops of up to 78% from their inflated valuations.

Nvidia (NVDA) - Implied Downside of 28%

  • Nvidia faces increasing competition, including customers developing in-house AI-GPUs, threatening its market dominance.

  • Insider selling and no recent insider purchases signal potential overvaluation.

Upstart Holdings (UPST) - Implied Downside of 76%

  • Upstart’s AI-driven loan approval model is struggling due to high interest rates and reduced loan demand.

  • The company’s growth has stalled, and it has been consistently unprofitable in the current high-rate environment.

  • A potential U.S. recession could further hurt Upstart’s business, which is cyclical and untested in economic downturns.

Palantir Technologies (PLTR) - Implied Downside of 78%

  • Palantir’s Gotham platform is limited to select government clients, capping its growth potential.

  • The company’s high valuation (93x forward earnings) leaves little room for error, making the stock risky at its current price.

  • Foundry, its business-focused platform, is still in its early stages, adding uncertainty to its future growth.

*this is not financial advice, obviously. You can get that from TikTok.😉

Amazon recently developed an AI-powered chatbot that provides employees with advice and coaching. The tool aims to help employees prepare for situations like meetings where they may disagree with their boss, offering feedback drawn from the collective experience of past evaluations.

  • Amazon recently returned to requiring employees to work five days a week in-person

  • The AI coach was trained on internal documents, including performance reviews and promotion criteria.

  • The chatbot offers personalized advice to employees based on company-wide experiences.

If the AI bot doesn’t work out, maybe they can hire a Ted Lasso bot instead.

Adobe has announced the launch of a free web app called "Content Authenticity" that aims to help users attach credentials to digital content that they create. This move comes as part of the company's efforts to address concerns about the proliferation of AI-generated images and misinformation online.

Content Credentials are like a “nutrition label” for digital content, serving as secure metadata that anyone can attach to their work to share information about themselves and provide context about how their content was created and edited.

- Andrew Cha, Adobe PR

  • Adobe's Content Authenticity web app makes it easy for creators to add Content Credentials to their work for free, helping protect against unauthorized use and ensuring proper attribution.

  • Content Credentials are available in Adobe apps like Photoshop, Lightroom, and Firefly, which is only trained on content Adobe has permission to use.

  • Creators can use the web app to indicate if they don’t want their work used to train AI models.

  • A free, public beta of the Adobe Content Authenticity web app will be available in Q1 2025.

The community has been extra sensitive to content attribution issues since it was revealed that Firefly, which they had postioned as “ethical AI”, had actually trained on some Midjourney images. You can read the full media release here.