In 2016, an artificial intelligence program called AlphaGo from Google’s DeepMind AI lab made history by defeating a champion player of the board game Go. Now Demis Hassabis, DeepMind’s cofounder and CEO, says his engineers are using techniques from AlphaGo to make an AI system dubbed Gemini that will be more capable than that behind OpenAI’s ChatGPT.
DeepMind’s Gemini, which is still in development, is a large language model that works with text and is similar in nature to GPT-4, which powers ChatGPT. But Hassabis says his team will combine that technology with techniques used in AlphaGo, aiming to give the system new capabilities such as planning or the ability to solve problems.
“At a high level you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models,” Hassabis says. “We also have some new innovations that are going to be pretty interesting.” Gemini was first teased at Google’s developer conference last month, when the company announced a raft of new AI projects. — Read More
Monthly Archives: June 2023
Introducing: Voice Library
Today, we [Eleven Labs] are releasing our latest development at the intersection of research, product and community: the Voice Library.
Voice Library is a community space for generating, sharing, and exploring a virtually infinite range of voices. Leveraging our proprietary Voice Design tool, Voice Library brings together a global collection of vocal styles for countless applications. — Read More
A New Kill Chain Approach to Disrupting Online Threats
If the internet is a battlefield between threat actors and the investigators who defend against them, that field has never been so crowded. The threats range from hacking to scams, election interference to harassment. The people behind them include intelligence services, troll farms, hate groups, and commercial companies of cyber mercenaries. The defenders include investigators at tech companies, universities, think tanks, government agencies, and media outlets.
… As long as the defenders remain siloed, without a common framework to understand and discuss threats, there is a risk that blended and cross-platform operations like these will be able to find a weak point and exploit it.
To help break down those siloes between investigators in different fields, companies, and institutions, we have developed a framework to analyze, map, and disrupt many different sorts of online threats: a kill chain for online operations. — Read More
Amazon’s vision: An AI model for everything
Matt Wood, vice president of product for Amazon Web Services, is at the tip of the spear of Amazon’s response in the escalating AI battle between the tech giants.
Much of the internet already runs on AWS’s cloud services and Amazon’s long game strategy is to create a single point of entry for companies and startups to tap into a rapidly increasing number of generative AI models, both of the open-source and closed-source variety.
Wood discussed this and other topics in an edited conversation. — Read More
Get a clue, says panel about buzzy AI tech: It’s being ‘deployed as surveillance’
Earlier today at a Bloomberg conference in San Francisco, some of the biggest names in AI turned up, including, briefly, Sam Altman of OpenAI, who just ended his two-month world tour, and Stability AI founder Emad Mostaque. Still, one of the most compelling conversations happened later in the afternoon, in a panel discussion about AI ethics.
Featuring Meredith Whittaker (pictured above), the president of the secure messaging app Signal; Credo AI co-founder and CEO Navrina Singh; and Alex Hanna, the director of Research at the Distributed AI Research Institute, the three had a unified message for the audience, which was: Don’t get so distracted by the promise and threats associated with the future of AI. It is not magic, it’s not fully automated and — per Whittaker — it’s already intrusive beyond anything that most Americans seemingly comprehend. — Read More
YouTube video translation is getting an AI-powered dubbing tool upgrade
YouTube is going to help its creators reach an international audience as the platform plans on introducing a new AI-powered dubbing tool for translating videos into other languages.
Announced at VidCon 2023, the goal of this latest endeavor is to provide a quick and easy way for creators to translate “at no cost” their content into languages they don’t speak. This can help out smaller channels as they may not have the resources to hire a human translator. To make this all possible, Amjad Hanif, vice president of Creator Products at YouTube, revealed the tool will utilize the Google-created Aloud plus the platform will be bringing over the team behind the AI from Area 120, a division of the parent company that frequently works on experimental tech. — Read More
Robots learn to perform chores by watching YouTube
Learning has been a holy grail in robotics for decades. If these systems are going to thrive in unpredictable environments, they’ll need to do more than just respond to programming — they’ll need to adapt and learn. What’s become clear the more I read and speak with experts is true robotic learning will require a combination of many solutions.
Video is an intriguing solution that’s been the centerpiece of a lot of recent work in the space. Roughly this time last year, we highlighted WHIRL (in-the-Wild Human Imitating Robot Learning), a CMU-developed algorithm designed to train robotic systems by watching a recording of a human executing a task.
This week, CMU Robotics Institute assistant professor Deepak Pathak is showcasing VRB (Vision-Robotics Bridge), an evolution to WHIRL. — Read More
AI and Moore’s Law: It’s the Chips, Stupid
Moore’s Law, which began with a random observation by the late Intel co-founder Gordon Moore that transistor densities on silicon substrates were doubling every 18 months, has over the intervening 60+ years been both borne-out yet also changed from a lithography technical feature to an economic law. It’s getting harder to etch ever-thinner lines, so we’ve taken as a culture to emphasizing the cost part of Moore’s Law (chips drop in price by 50 percent on an area basis (dollars per acre of silicon) every 18 months). We can accomplish this economic effect through a variety of techniques including multiple cores, System-On-Chip design, and unified memory — anything to keep prices going-down.
I predict that Generative Artificial Intelligence is going to go a long way toward keeping Moore’s Law in force and the way this is going to happen says a lot about the chip business, global economics, and Artificial Intelligence, itself. — Read More
The people paid to train AI are outsourcing their work… to AI
A significant proportion of people paid to train AI models may be themselves outsourcing that work to AI, a new study has found.
It takes an incredible amount of data to train AI systems to perform specific tasks accurately and reliably. Many companies pay gig workers on platforms like Mechanical Turk to complete tasks that are typically hard to automate, such as solving CAPTCHAs, labeling data and annotating text. This data is then fed into AI models to train them. The workers are poorly paid and are often expected to complete lots of tasks very quickly.
No wonder some of them may be turning to tools like ChatGPT to maximize their earning potential. But how many? — Read More
AI could shore up democracy – here’s one way
It’s become fashionable to think of artificial intelligence as an inherently dehumanizing technology, a ruthless force of automation that has unleashed legions of virtual skilled laborers in faceless form. But what if AI turns out to be the one tool able to identify what makes your ideas special, recognizing your unique perspective and potential on the issues where it matters most?
You’d be forgiven if you’re distraught about society’s ability to grapple with this new technology. So far, there’s no lack of prognostications about the democratic doom that AI may wreak on the U.S. system of government. There are legitimate reasons to be concerned that AI could spread misinformation, break public comment processes on regulations, inundate legislators with artificial constituent outreach, help to automate corporate lobbying, or even generate laws in a way tailored to benefit narrow interests.
But there are reasons to feel more sanguine as well. — Read More
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