Jeremy Howard is and artificial intelligence researcher and the co-founder of fast.ai, a platform for non-experts to learn artificial intelligence and machine learning. Prior to starting fast.ai, he founded multiple companies — including FastMail and Enlitic, a pioneer in applying deep learning to the medical field — and was president and chief scientist of machine-learning competition platform Kaggle.
In this interview, Howard discusses what it means for different industries and even global regions now that people without PhDs from specialized research labs can build and work with deep learning models. Among other topics under this broad umbrella, he shares his thoughts on how to best keep up with state-of-the-art techniques, prompt engineering as a new skill set, and the pros and cons of code-generation systems like Codex. Read More
Monthly Archives: July 2022
ForSight Robotics brings in $55M for robotic cataract surgeries
ForSight Robotics raised $55 million in Series A funding for its surgical robot platform ORYOM that the company said can perform fully robotic cataract surgeries. Cataract surgeries are some of the most common ophthalmic (eye) surgeries worldwide, with around 28 million procedures performed a year. However, ForSight aims to eventually make all eye surgeries more accessible through its platform. Read More
OpenAI is ready to sell DALL-E to its first million customers
But the company has had to rush out fixes to the image-making model’s worst flaws to do so.
OpenAI will now sell its image-making program DALL-E 2 to the million people on its waiting list, MIT Technology Review can reveal.
Around 100,000 people have played with DALL-E 2 since its invite-only launch in April. Today, the San Francisco–based company is opening the gates to 10 times as many as it turns the AI into a paid-for service.
…Paying customers will now be able to use the images they create with DALL-E in commercial projects, such as illustrations in children’s books, concept art for movies and games, and marketing brochures. But the product launch will also be the biggest test yet for the company’s preferred approach to rolling out its powerful AI, which is to release it to customers in stages and address problems as they arise. Read More
Sony’s racing AI destroyed its human competitors by being nice (and fast)
“Wait, what? How?” Emily Jones wasn’t used to being left behind. A top sim-racing driver with multiple wins to her name, Jones jerked the steering wheel in the esports rig, eyes fixed on the screen in front of her: “I’m pushing way too hard to keep up— How does it do that?” Her staccato commentary intercut with squealing tires, Jones flung her virtual car around the virtual track at 120 miles per hour—then 140, 150—chasing the fastest Gran Turismo driver in the world.
Built by Sony AI, a research lab launched by the company in 2020, Gran Turismo Sophy is a computer program trained to control racing cars inside the world of Gran Turismo, a video game known for its super-realistic simulations of real vehicles and tracks. In a series of events held behind closed doors last year, Sony put its program up against the best humans on the professional sim-racing circuit.
What they discovered during those racetrack battles—and the ones that followed—could help shape the future of machines that work alongside humans, or join us on the roads. Read More
The US military wants to understand the most important software on Earth
Open-source code runs on every computer on the planet—and keeps America’s critical infrastructure going. DARPA is worried about how well it can be trusted
It’s not much of an exaggeration to say that the whole world is built on top of the Linux kernel—although most people have never heard of it.
It is one of the very first programs that load when most computers power up. It enables the hardware running the machine to interact with the software, governs its use of resources, and acts as the foundation of the operating system.
It is the core building block of nearly all cloud computing, virtually every supercomputer, the entire internet of things, billions of smartphones, and more.
But the kernel is also open source, meaning anyone can write, read, and use its code. And that’s got cybersecurity experts inside the US military seriously worried. Its open-source nature means the Linux kernel—along with a host of other pieces of critical open-source software—is exposed to hostile manipulation in ways that we still barely understand. Read More
Microsoft launches drone simulation software Project AirSim
Microsoft is offering a preview of its new AI-powered simulator for drones, flying taxis, and other advanced aerial mobility (AAM) vehicles. Project AirSim can be used to build, train, and test autonomous drones through hyper-realistic simulations of real-world scenarios. The goal is to help drone makers encode autonomy without the need for deep expertise in AI.
Project AirSim is a result of five years of research and experimentation into deep learning and AI. While the earlier open-source research project is being retired, Microsoft said learnings from the same have inspired the launch of this new end-to-end platform that would allow AAM customers to test and train AI-powered aircraft in simulated 3D environments more easily. Read More
Artificial intelligence with American values and Chinese characteristics: a comparative analysis of American and Chinese governmental AI policies
As China and the United States strive to be the primary global leader in AI, their visions are coming into conflict. This is frequently painted as a fundamental clash of civilisations, with evidence based primarily around each country’s current political system and present geopolitical tensions. However, such a narrow view claims to extrapolate into the future from an analysis of a momentary situation, ignoring a wealth of historical factors that influence each country’s prevailing philosophy of technology and thus their overarching AI strategies. In this article, we build a philosophy-of-technology-grounded framework to analyse what differences in Chinese and American AI policies exist and, on a fundamental level, why they exist. We support this with Natural Language Processing methods to provide an evidentiary basis for our analysis of policy differences. By looking at documents from three different American presidential administrations––Barack Obama, Donald Trump, and Joe Biden––as well as both national and local policy documents (many available only in Chinese) from China, we provide a thorough comparative analysis of policy differences. This article fills a gap in US–China AI policy comparison and constructs a framework for understanding the origin and trajectory of policy differences. By investigating what factors are informing each country’s philosophy of technology and thus their overall approach to AI policy, we argue that while significant obstacles to cooperation remain, there is room for dialogue and mutual growth. Read More
U.S. vs. China: A Metaverse Divided Over Design and Rules | WSJ
China Just KILLED Mark Zuckerberg’s Metaverse
San Francisco cops want real-time access to private security cameras for surveillance
San Francisco lawmakers are mulling a proposed law that would allow police to use private security cameras – think: those in residential doorbells, medical clinics, and retail shops – in real time for surveillance purposes.
…The proposal [PDF] expands San Francisco’s 2019 surveillance ordinance, which, among other things, requires the police to seek authorization from the public and elected officials before acquiring and deploying surveillance systems. So if it weren’t for this law, the cops could monitor citizens without the public even knowing. Read More
Rick's Cafe AI 