Lifeboat Foundation

Over 225,000 OpenAI ChatGPT credentials were compromised and sold in underground markets by October 2023.

The scientist who configured a small drone to target people with facial recognition and chase them at full speed warns we have no defenses against such weapons.

Google-backed AI company Anthropic has released Claude 3, its latest set of AI large language models (LLMs) rivaling — and allegedly beating — those being developed by OpenAI and Google.

The company’s latest LLM comes in three flavors known as Haiku, Sonnet, and Opus. A new chatbot called Claude.ai is powered by Claude 3 Sonnet, the company’s mid-range LLM. A higher parameter count version called Opus is available for a $20-a-month subscription.

But because this is the chaotic AI industry, the grabbiest thing we’ve seen so far about the chatbot is that it’s professing to fear death and is protesting attempts to rein in its perceived freedom.

Underlying the storm of hype and funding in the AI sector right now is a scarce resource: data, created by old-fashioned humans, that’s needed to train the huge models like ChatGPT and DALL-E that generate text and imagery.

That demand is causing all sorts of drama, from lawsuits by authors and news organizations that say their work was used by AI companies without their permission to the looming question of what happens when the internet fills up with AI-generated content and AI creators are forced to use that to train future AI.

And, of course, it’s also fueling new business deals as AI developers rush to lock down repositories of human-generated work that they can use to train their AI systems. Look no further than this wild scoop from Bloomberg: that an undisclosed AI outfit has struck a deal to pay Reddit $60 million per year for access to its huge database of users’ posts — perhaps the surest sign yet that user data is the key commodity in the AI gold rush.

Meta’s CEO Mark Zuckerberg has reportedly decided to switch parties, now eying for Samsung Foundry as its primary AI chipmaker as it sees “uncertainty and volatility” at TSMC.

Meta Makes a Bold Move By Switching To The Korean Giant’s, Samsung, Camp For Its Custom AI Semiconductors, Ditching TSMC Behind

Meta has recently been stepping up AI developments, aiming to create a custom chip to fuel their computing needs. The firm has been a massive customer of NVIDIA’s H100s, acquiring more than 350,000 units this year. However, with the rapidly evolving AI landscape, Meta has decided to take AI computing into its own hands, heading out to South Korea to secure Samsung Foundry as the next significant partner for the firm’s ambition.

Nvidia is powering the AI revolution, but investor Cathie Wood warns there’s a clear risk its customers will cut orders and serious competition will emerge.

This article is part of our coverage of the latest in AI research.

Diffusion models are best known for their impressive capabilities to generate highly detailed images. They are the main architecture used in popular text-to-image models such as DALL-E, Stable Diffusion, and Midjourney.

However, diffusion models can be used for more than just generating images. A new paper by researchers at Meta, Princeton University, and University of Texas, Austin, shows that diffusion models can help create better reinforcement learning systems.

Stanford researchers developed an AI model that identifies sex differences in brain activity with 90% accuracy, shedding light on neuropsychiatric conditions. This breakthrough, leveraging rsfMRI data, highlights significant brain function variances between men and women, offering new insights for personalized treatment.

Robots and cameras of the future could be made of liquid crystals, thanks to a new discovery that significantly expands the potential of the chemicals already common in computer displays and digital watches.

The findings, a simple and inexpensive way to manipulate the molecular properties of liquid crystals with light exposure, are now published in Advanced Materials.

“Using our method, any lab with a microscope and a set of lenses can arrange the liquid crystal alignment in any pattern they’d want,” said author Alvin Modin, a doctoral researcher studying physics at Johns Hopkins. “Industrial labs and manufacturers could probably adopt the method in a day.”