Google Announces the Launch of Gemini, Its Largest AI Model

Google is closing the year by heralding 2024 as the “Gemini era,” with the introduction of its “most capable and general AI model yet,” Gemini 1.0. This new foundation model is optimized for three different use-case sizes: Ultra, Pro and Nano. As a result, Google is releasing a new, Gemini-powered version of its Bard chatbot, available to English speakers in the U.S. and 170 global regions. Google touts Gemini as built from the ground up for multimodality, reasoning across text, images, video, audio and code. However, Bard will not as yet incorporate Gemini’s ability to analyze sound and images. Continue reading Google Announces the Launch of Gemini, Its Largest AI Model

Stability AI Intros Real-Time Text-to-Image Generation Model

Stability AI, developer of Stable Diffusion (one of the leading visual content generators, alongside Midjourney and DALL-E), has introduced SDXL Turbo — a new AI model that demonstrates more of the latent possibilities of the common diffusion generation approach: images that update in real time as the user’s prompt updates. This feature was always a possibility even with previous diffusion models given text and images are comprehended differently across linear time, but increased efficiency of generation algorithms and the steady accretion of GPUs and TPUs in a developer’s data center makes the experience more magical. Continue reading Stability AI Intros Real-Time Text-to-Image Generation Model

Cerebras, G42 Partner on a Supercomputer for Generative AI

Cerebras Systems has unveiled the Condor Galaxy 1, powered by nine networked supercomputers designed for a total of 4 exaflops of AI compute via 54 million cores. Cerebras says the CG-1 greatly accelerates AI model training, completing its first run on a large language AI trained for Abu Dhabi-based G42 in only 10 days. Cerebras and G42 have partnered to offer the Santa Clara, California-based CG-1 as a cloud service, positioning it as an alternative to Nvidia’s DGX GH200 cloud supercomputer. The companies plan to release CG-2 and CG-3 in early 2024. Continue reading Cerebras, G42 Partner on a Supercomputer for Generative AI

Meta In-House Chip Designs Include Processing for AI, Video

Meta Platforms has shared additional details on its next generation of AI infrastructure. The company has designed two custom silicon chips, including one for training and running AI models and eventually powering metaverse functions like virtual reality and augmented reality. Another chip is tailored to optimize video processing. Meta publicly discussed its internal chip development last week ahead of a Thursday virtual event on AI infrastructure. The company also showcased an AI-optimized data center design and talked about phase two of deployment of its 16,000 GPU supercomputer for AI research. Continue reading Meta In-House Chip Designs Include Processing for AI, Video

Facebook to Develop Live Video Filtering Chips for Faster AI

Facebook has used Intel CPUs for many of its artificial intelligence services, but the company is changing course to adapt to the pressing need to better filter live video content. At the Viva Technology industry conference in Paris, Facebook chief AI scientist Yann LeCun stated that the company plans to make its own chips for filtering video content, because more conventional methods suck up too much energy and compute power. Last month, Bloomberg reported that the company is building its own semiconductors. Continue reading Facebook to Develop Live Video Filtering Chips for Faster AI

Google Offers Its AI Chips to All Comers via Cloud Computing

Google, which created tensor processing units (TPUs) for its artificial intelligence systems some years ago, will now make those computer chips available to other companies via its cloud computing service. Google is currently focusing on computer vision technology, which allows computers to recognize objects; Lyft used these chips for its driverless car project. Amazon is also building its own AI chips for use with the Alexa-powered Echo devices to shave seconds off its response time and potentially increase sales. Continue reading Google Offers Its AI Chips to All Comers via Cloud Computing

Microsoft Speeds Up AI with New Programmable FPGA Chips

In 2012, Microsoft chief executive Steve Ballmer and computer chip researcher Doug Burger believed they had found the future of computing: chips that could be programmed for specific tasks, dubbed field programmable gate arrays (FPGAs). Project Catapult, as it was called, was intended to shift the underlying technology of all Microsoft servers in that direction. FPGAs now form the basis of Bing. Soon, the specialized chips will be capable of artificial intelligence at a tremendous speed — 23 milliseconds versus four seconds. Continue reading Microsoft Speeds Up AI with New Programmable FPGA Chips

Google Develops its Own Chip to Speed Up Machine Learning

Google has just built its own chip as part of its efforts to speed up artificial intelligence developments. The company revealed that this is just the first of many chips it plans to develop and build. At the same time, an increasing number of businesses are migrating to the cloud, lessening the need for servers that rely on chips to function. That’s led some to believe that Google and other Internet titans that follow its lead will impact the future of the chip industry, particularly such stalwarts as Intel and Nvidia. Continue reading Google Develops its Own Chip to Speed Up Machine Learning