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Eric Schmidt's AI Prophecies, and AI Predicts Disaster Tipping Points
Plus, Rent Live Human Neurons for $500 a Month š§
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The weekās most interesting and relevant AI news and analysis
This Week in AI
Matt Garman, CEO of Amazon Web Services, told employees that in about two years, āitās possible that most developers are not coding.ā He expects AI to handle most of the coding, allowing developers to spend more time understanding customer needs and guiding AI to create software. Business Insider obtained his remarks after they were leaked. Perhaps Garman was thinking about Devin, the AI software engineer created by Cognition AI, that is currently a leader in the space.
Medical health records giant Epic is bringing new generative AI features to its platforms to streamline charting, ease clinician workloads, and improve patient experiences. The system augments doctor-patient communication by automatically drafting responses, saving doctors up to half a minute a message. Across 150 healthcare systems, itās drafting one million messages PER MONTH. Thatās a lot of clinician minutes saved, especially when 40%-60% of clinicians report burnout due to staff shortages. In testing, patients prefer so-called augmented responses, remarking they seem more humanāPerhaps more of a commentary on clinician overload than anything else. The Epic system can auto-chart patient-doctor conversations, enabling the clinician to focus on their patient rather than note-taking. Epic says they have another 100 generative AI projects in flight.
Researchers have published details of a new AI model that predicts the onset of catastrophic tipping points in complex systems, a task that has proven very difficult, until now. Tipping points can occur in any complex system, for example, financial markets, ecological systems, climate change, or urban traffic networks. Dramatic transformations in complex systems are poorly understood, and scientistsā predictions often rely on oversimplified models, making predictions shaky. The new AI approach improves prediction by modeling complex interactions and crunching far more data than a human mind can comprehend.
Quick Hits
OpenAI and CondĆ© Nast Deal - The publishers of The New Yorker, Vogue, Bon AppĆ©tit, Wired, and Vanity Fair signed a multiyear licensing deal related to ChatGPT and OpenAIās new Google competitor, SearchGPT. š
U.S. Government Bans AI-generated Reviews - The Federal Trade Commission plans to crack down on fake reviews of all kinds, including AI-generated ones.
AI Could Turn Anyone into an Expert Animal Tracker - An AI system named WildTrack can successfully identify 17 species from their footprints and will soon identify individual animals. š¾
Alien: Romulus Brings Back Dead Actor with AI - Ian Holm died in 2020, but thanks to AI, he plays a role in the latest Alien franchise movie. Controversy and outrage have ensued.
Trump Upsets Swifties - Furious Taylor Swift fans arenāt happy after Trump shared a fake endorsement by the singer featuring AI-generated images.
Video: AI Music Made by a Musician š¶
In this thoughtful and thought-provoking video, experienced musician Jonny Keely talks about using Udio to help him make a song and the huge questions it poses for the future of music. The song he creates with AI is impressive, and Keely draws a sharp contrast by singing a version himself. Youāll be surprised by which he prefers. Itās worth watching if only to understand just how good AI music generators are today. (10m)
AI Tech and Innovation
Former Google CEO and now AI mega investor Eric Schmidt recently spoke to students at Standford University and dropped some big ideas on the audience. Schmidt believes the potent combination of enormous context windows, agentic AI, and text-to-action models will lead to new AI capabilities that accelerate innovation exponentially within just a few years. He also predicts the scale of AI investments will skyrocket. At Schmidt's request, online copies of the video interview keep being deleted due to his comments about Googleās remote work policy, but hereās a link to try. š®
Transistors power the modern world but suck enormous amounts of power. By comparison, the neurons in our brain are incredibly energy efficient. The human brain consumes only about 25W while working flat out. Our brains prove that high-level intelligence doesnāt have to consume megawatts of power. Scientists are now building computers using synthetic biology to grow clusters of āorganoids,ā lab-grown 3D structures that resemble human tissue. Swiss company FinalSpark has built a āNeuroplatformā that scientists can rent over the net for $500 a month. Their goal is to create AI that consumes 100,000 times less energy than traditional methods. š§
All chipmakers are eyeing Nvidiaās fat margins and profits. One reason Nvidia has such a strong leadership position is that it doesnāt just sell chips; it sells complete AI solutions, including chips, boards, networking, server building blocks, and a comprehensive software stack. AMD picked up server builder ZT Systems for a cool $4.9 billion, so it has āa more complete offeringā and an edge in designing systems. Chip designers constantly need feedback from systems and model builders as they create their next-generation products.
If youāre in IT and trying to decide which large language model to use for your next project, this paper might help you choose. It comprehensively benchmarks 180 leading models and evaluates their strengths and weaknesses. š
AI Insights
One of the great promises of AI, particularly artificial general intelligence, is the ability to automate or semi-automate scientific research, thereby accelerating discovery and yielding incredible breakthroughs in medicine, material science, and energy. This has been a significant focus of AI research labs like DeepMind with their AlphaFold and GNoME platforms. Now Sakana AI has announced an āAI scientistā designed to automate scientific discovery and write research papers. Some have described its output as āendless scientific slopā and argued that AI tools should support scientists, not seek to replace them. š¬
A debate is raging in AI circles about the benefits and risks of an open-source approach to AI. Open-source projects gave us many of the internetās underpinnings. Linux, WordPress, and Apache rule the web. Kubernetes and Docker make the cloud possible. Facebook, Instagram, Reddit, YouTube, and Spotify rely on open-source relational databases MySQL and PostgreSQL. Many AI startups build on top of open-source AI models from Meta, Mistral, Salesforce, and other companies to add value and fine-tune them for specific applications. Others argue that as AI models become more powerful, open-source AI could enable bad actors and amplify AI safety risks.
Which country do you think has the highest consumer use of ChatGPT as a percentage of the population? The United States isnāt even in the top ten. In the leading country, 45% of consumers are using ChatGPT.
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