The Azure Maia 100 and Cobalt 100 chips are the first two custom silicon chips designed by Microsoft for its cloud infrastructure.
Microsoft launched its big AI push earlier this year as part of its Bing search engine, integrating a ChatGPT-like interface directly into its search results. Now less than a year later, it’s dropping the Bing Chat branding and moving to Microsoft Copilot, the new name for the chat interface you might have used in Bing, Microsoft Edge, and Windows 11.
Microsoft initially talked up the Google search competition for its AI ambitions earlier this year, but it now looks like it has its sights set on ChatGPT instead. The Bing Chat rebranding comes just days after OpenAI revealed 100 million people are using ChatGPT on a weekly basis. Despite a close partnership worth billions, Microsoft and OpenAI continue to compete for the same customers seeking out AI assistants, and Microsoft is clearly trying to position Copilot as the option for consumers and businesses.
“Bing Chat and Bing Chat Enterprise will now simply become Copilot,” explains Colette Stallbaumer, general manager of Microsoft 365. The official name change comes just a couple of months after Microsoft picked Copilot as its branding for its chatbot inside Windows 11. At the time it wasn’t clear that the Bing Chat branding would fully disappear, but it is today.
Generative AI (GenAI) sits at the center of the next wave of digital and data transformation.
Dell Technologies is working with both Meta and Hugging Face to help accelerate the adoption of generative AI (GenAI) in the enterprise.
OpenAI has placed a temporary ban on new sign-ups for ChatGPT Plus following a surge in demand for the service.
ChatGPT Plus is the $20 per month, premium version of the now infamous chatbot. It includes a host of extra features, including the recently added GPTs—personalized chatbots that are focused on a specific task, such as teaching you how to play chess or negotiating better business deals.
OpenAI CEO Sam Altman claims a surge in usage of the service since the launch of GPTs and other new features announced at its recent developer conference has forced the company to act.
Summary: Researchers developed an experimental computing system, resembling a biological brain, that successfully identified handwritten numbers with a 93.4% accuracy rate.
This breakthrough was achieved using a novel training algorithm providing continuous real-time feedback, outperforming traditional batch data processing methods which yielded 91.4% accuracy.
The system’s design features a self-organizing network of nanowires on electrodes, with memory and processing capabilities interwoven, unlike conventional computers with separate modules.
One of the more unexpected products to launch out of this year’s Microsoft Ignite conference is a tool that can create a photorealistic avatar of a person and animate that avatar saying things that the person didn’t necessarily say.
Called Azure AI Speech text to speech avatar, the new feature, available in public preview as of today, lets users generate videos of an avatar speaking by uploading images of a person they wish the avatar to resemble and writing a script. Microsoft’s tool trains a model to drive the animation, while a separate text-to-speech model — either prebuilt or trained on the person’s voice — “reads” the script aloud.
“With text to speech avatar, users can more efficiently create video … to build training videos, product introductions, customer testimonials [and so on] simply with text input,” writes Microsoft in a blog post. “You can use the avatar to build conversational agents, virtual assistants, chatbots and more.”
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Fine-tuning large language models (LLM) has become an important tool for businesses seeking to tailor AI capabilities to niche tasks and personalized user experiences. But fine-tuning usually comes with steep computational and financial overhead, keeping its use limited for enterprises with limited resources.
To solve these challenges, researchers have created algorithms and techniques that cut the cost of fine-tuning LLMs and running fine-tuned models. The latest of these techniques is S-LoRA, a collaborative effort between researchers at Stanford University and University of California-Berkeley (UC Berkeley).
It’s worth noting that Airloom’s new wind turbine can be configured vertically or horizontally and that it can be deployed offshore as well as on land.
“For decades, the wind industry has lowered the cost of energy production by scaling ever larger turbines. Although this has been extremely successful in driving down overall costs, the approach now faces challenges in terms of both siting and cost of materials,” said Carmichael Roberts of Breakthrough Energy Ventures in a press release. “Airloom’s unique approach can solve both these problems, opening new market opportunities for wind energy that will further drive down costs. We look forward to Neal’s leadership in bringing this revolutionary technology into the market.”
With small-scale prototypes already up and running, the company plans to use its seed funding for research and development of the Airloom wind energy test device, which is designed to produce 50 kilowatts (kW) of electricity. Future systems are expected to be megawatt-scale and deployed hundreds of megawatts at a time in utility-scale wind farms.
The ability to jump forward and backwards in time has long fascinated science fiction writers and physicists alike. So is it really possible to travel into the past and the future?