Just as the periodic table is foundational to chemistry and the Human Genome Project revolutionized modern genetics, researchers at the Allen Institute for Brain Science have teamed up with Amazon Web Services to create what could become a “transformative” new resource for the field of neuroscience.
AWS on Wednesday announced its technology will support the Allen Institute as it builds a map of the human brain, called the Brain Knowledge Platform. This platform, the first of its kind, is designed to be a complete reference of individual cells in the brain, and should eventually serve as the world’s largest open-source brain cell database. — Read More
Recent Updates Page 189
Introducing Google’s Secure AI Framework
The potential of AI, especially generative AI, is immense. However, in the pursuit of progress within these new frontiers of innovation, there needs to be clear industry security standards for building and deploying this technology in a responsible manner. That’s why today we are excited to introduce the Secure AI Framework (SAIF), a conceptual framework for secure AI systems.
SAIF is inspired by the security best practices — like reviewing, testing and controlling the supply chain — that we’ve applied to software development, while incorporating our understanding of security mega-trends and risks specific to AI systems. — Read More
Leveraging FastAPI, OpenAI, and SQLAlchemy for Natural Language SQL Queries
SQL (Structured Query Language) is the standard language for managing and manipulating relational databases. What if we could interact with databases using natural language queries?
In this post we show how you can use SQL to load a dataframe to a database, write a prompt to query it, and connect this to a FastAPI application for deployment and enabling users to interact with the database. — Read More
How open-source LLMs are challenging OpenAI, Google, and Microsoft
In the past few years, it seemed that wealthy tech companies would be able to monopolize the growing market for large language models (LLM). And recent earnings calls from big tech companies suggested they are in control. Microsoft’s announcements, in particular, show that the company has created a billion-dollar business from its AI services, including through Azure OpenAI Services and the workloads OpenAI runs on its cloud infrastructure.
However, a recently leaked internal document from Google indicates that the market share of big tech is not as secure as it seems thanks to advances in open-source LLMs. In short, the document says “We have no moat, and neither does OpenAI.” The dynamics of the market are gradually shifting from “bigger is better” to “cheaper is better,” “more efficient is better,” and “customizable is better.” And while there will always be a market for cloud-based LLM and generative AI products, customers now have open-source options to explore as well. — Read More
Google DeepMind’s game-playing AI just found another way to make code faster
The AI-generated algorithms are already being used by millions of developers.
DeepMind’s run of discoveries in fundamental computer science continues. Last year the company used a version of its game-playing AI AlphaZero to find new ways to speed up the calculation of a crucial piece of math at the heart of many different kinds of code, beating a 50-year-old record.
Now it has pulled the same trick again—twice. Using a new version of AlphaZero called AlphaDev, the UK-based firm (recently renamed Google DeepMind after a merge with its sister company’s AI lab in April) has discovered a way to sort items in a list up to 70% faster than the best existing method.
It has also found a way to speed up a key algorithm used in cryptography by 30%. These algorithms are among the most common building blocks in software. Small speed-ups can make a huge difference, cutting costs and saving energy. — Read More
Google Cloud partners with Mayo Clinic on new AI tool to improve patient care
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
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
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