Google Cloud has announced a new partnership with Mayo Clinic that will introduce a new Artificial Intelligence tool that aims to improve the efficiency of healthcare throughout the United States.
The initial focus of the collaboration will establish a new search tool powered by Google Cloud’s Generative AI software that would improve clinical workflows by making it easier for doctors and researchers to quickly track down patient information, the tech giant said. — Read More
Monthly Archives: June 2023
Existential Risk? I Don’t Get It! (by Andrew Ng)
Prominent computer scientists fear that AI could trigger human extinction. It’s time to have a real conversation about the realistic risks.
Last week, safe.org asserted that “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.” This statement was signed by AI scientists who I really respect including Yoshua Bengio and Geoffrey Hinton. It received widespread media coverage.
I have to admit that I struggle to see how AI could pose any meaningful risk for our extinction. AI has risks like bias, fairness, inaccurate outputs, job displacement, and concentration of power. But I see AI’s net impact as a massive contribution to society. It’s saving lives by improving healthcare and making cars safer, improving education, making healthy food and numerous other goods and services more affordable, and democratizing access to information. I don’t understand how it can lead to human extinction. — Read More
RedPajama 7B now available, instruct model outperforms all open 7B models on HELM benchmarks
The RedPajama project aims to create a set of leading open-source models and to rigorously understand the ingredients that yield good performance. In April we released the RedPajama base dataset based on the LLaMA paper, which has worked to kindle rapid innovation in open-source AI.
The 5 terabyte dataset has been downloaded thousands of times and used to train over 100 models! — Read More
Why AI Will Save the World (by Marc Andreessen)
The era of Artificial Intelligence is here, and boy are people freaking out.
Fortunately, I am here to bring the good news: AI will not destroy the world, and in fact may save it.
First, a short description of what AI is: The application of mathematics and software code to teach computers how to understand, synthesize, and generate knowledge in ways similar to how people do it. AI is a computer program like any other – it runs, takes input, processes, and generates output. AI’s output is useful across a wide range of fields, ranging from coding to medicine to law to the creative arts. It is owned by people and controlled by people, like any other technology.
A shorter description of what AI isn’t: Killer software and robots that will spring to life and decide to murder the human race or otherwise ruin everything, like you see in the movies.
An even shorter description of what AI could be: A way to make everything we care about better. — Read More
What ChatGPT Can and Can’t Do for Intelligence
In November 2022, ChatGPT emerged as a front-runner among artificial intelligence (AI) large language models (LLMs), capturing the attention of the CIA and other U.S. defense agencies. General artificial intelligence—AI with flexible reasoning like that of humans—is still beyond the technological horizon and might never happen. But most experts agree that LLMs are a major technological step forward. The ability of LLMs to produce useful results in some tasks, and entirely miss the mark on others, offers a glimpse into the capabilities and constraints of AI in the coming decade.
The prospects of ChatGPT for intelligence are mixed. On the one hand, the technology appears “impressive,” and “scarily intelligent,” but on the other hand, its own creators warned that “it can create a misleading impression of greatness.” In the absence of an expert consensus, researchers and practitioners must explore the potential and downsides of the technology for intelligence. — Read More
Welcome to the new surreal. How AI-generated video is changing film
The Frost nails its uncanny, disconcerting vibe in its first few shots. Vast icy mountains, a makeshift camp of military-style tents, a group of people huddled around a fire, barking dogs. It’s familiar stuff, yet weird enough to plant a growing seed of dread. There’s something wrong here.
“Pass me the tail,” someone says. Cut to a close-up of a man by the fire gnawing on a pink piece of jerky. It’s grotesque. The way his lips are moving isn’t quite right. For a beat it looks as if he’s chewing on his own frozen tongue.
Welcome to the unsettling world of AI moviemaking. “We kind of hit a point where we just stopped fighting the desire for photographic accuracy and started leaning into the weirdness that is DALL-E,” says Stephen Parker at Waymark, the Detroit-based video creation company behind The Frost.
The Frost is a 12-minute movie in which every shot is generated by an image-making AI. It’s one of the most impressive—and bizarre—examples yet of this strange new genre. You can watch the film below in an exclusive reveal from MIT Technology Review. — Read More
The Falcon has landed in the Hugging Face ecosystem
Falcon is a new family of state-of-the-art language models created by the Technology Innovation Institute in Abu Dhabi, and released under the Apache 2.0 license. Notably, Falcon-40B is the first “truly open” model with capabilities rivaling many current closed-source models. This is fantastic news for practitioners, enthusiasts, and industry, as it opens the door for many exciting use cases.
In this blog, we will be taking a deep dive into the Falcon models: first discussing what makes them unique and then showcasing how easy it is to build on top of them (inference, quantization, finetuning, and more) with tools from the Hugging Face ecosystem. — Read More
Ex-Google Officer Finally Speaks Out On The Dangers Of AI! – Mo Gawdat
The Illusion of China’s AI Prowess
Regulating AI Will Not Set America Back in the Technology Race
The artificial intelligence revolution has reached Congress. The staggering potential of powerful AI systems, such as OpenAI’s text-based ChatGPT, has alarmed legislators, who worry about how advances in this fast-moving technology might remake economic and social life. Recent months have seen a flurry of hearings and behind-the-scenes negotiations on Capitol Hill as lawmakers and regulators try to determine how best to impose limits on the technology. But some fear that any regulation of the AI industry will incur a geopolitical cost. In a May hearing at the U.S. Senate, Sam Altman, the CEO of OpenAI, warned that “a peril” of AI regulation is that “you slow down American industry in such a way that China or somebody else makes faster progress.” That same month, AI entrepreneur Alexandr Wang insisted that “the United States is in a relatively precarious position, and we have to make sure we move fastest on the technology.” Indeed, the notion that Washington’s propensity for red tape could hurt it in the competition with Beijing has long occupied figures in government and in the private sector. Former Google CEO Eric Schmidt claimed in 2021 that “China is not busy stopping things because of regulation.” According to this thinking, if the United States places guardrails around AI, it could end up surrendering international AI leadership to China. — Read More
StyleDrop: Text-To-Image Generation in Any Style
We present StyleDrop that enables the generation of images that faithfully follow a specific style, powered by Muse, a text-to-image generative vision transformer. StyleDrop is extremely versatile and captures nuances and details of a user-provided style, such as color schemes, shading, design patterns, and local and global effects. StyleDrop works by efficiently learning a new style by fine-tuning very few trainable parameters (less than 1% of total model parameters), and improving the quality via iterative training with either human or automated feedback. Better yet, StyleDrop is able to deliver impressive results even when the user supplies only a single image specifying the desired style. An extensive study shows that, for the task of style tuning text-to-image models, Styledrop on Muse convincingly outperforms other methods, including DreamBooth and Textual Inversion on Imagen or Stable Diffusion. — Read More
Rick's Cafe AI 