Skip to main content

China’s DeepSeek AI is hitting Nvidia where it hurts

The DeepSeek whale logo on a blue background.
The market value of US AI companies is taking a tumble. | Image: DeepSeek

A chatbot made by Chinese artificial intelligence startup DeepSeek has rocketed to the top of Apple’s App Store charts in the US this week, dethroning OpenAI’s ChatGPT as the most downloaded free app. The eponymous AI assistant is powered by DeepSeek’s open-source models, which the company says can be trained at a fraction of the cost using far fewer chips than the world’s leading models. Shares for Nvidia, the biggest global supplier of advanced AI chips, are currently down over 12 percent in pre-market training,

Downloads for the app exploded shortly after DeepSeek released its new R1 reasoning model on January 20th, which is designed for solving complex problems and reportedly performs as well as OpenAI’s o1 on certain benchmarks. R1 was built on the V3 LLM DeepSeek released in December, which the company claims is on par with GPT-4o and Anthropic’s Claude 3.5 Sonnet, and cost less than $6 million to develop. By contrast, OpenAI CEO Sam Altman has said GPT-4 cost over $100 million to train.

DeepSeek also claims to have needed only about 2,000 specialized chips from Nvidia to train V3, compared to the 16,000 or more required to train leading models, according to the New York Times. These unverified claims are leading developers and investors to question the compute-intensive approach favored by the world’s leading AI companies. And if true, it means that DeepSeek engineers had to get creative in the face of trade restrictions meant to ensure US domination of AI.

Nvidia, Microsoft, OpenAI, and Meta are investing billions into AI data centers — $500 billion alone for the Stargate Project, of which $100 billion is thought to be earmarked for Nvidia. Investors and analysts are now wondering if that’s money well spent, with Nvidia, Microsoft, and other companies with substantial stakes in maintaining the AI status quo all trending downward in pre-market trading.



from The Verge - All Posts https://ift.tt/XlAx4zn
Labels:

Comments

Post a Comment

Popular posts from this blog

Pandora Stories lets artists add commentary to their own playlists

Pandora launched Stories today, a tool that lets artists and creators add voice commentary to their own playlists. The Stories feature merges podcasts with music playlists, and is meant for artists to add context to an album, or for podcasters to experiment with new storytelling formats. The feature is part of Pandora AMP, the streaming service’s free Artist Marketing Platform that helps creators promote their work. To kick off the launch, Pandora’s prepared some Stories by artists like John Legend and Daddy Yankee, who tell listeners their personal stories interspersed between their own songs. There’s also a Stories playlist called Love Songs That Aren’t Really Love Songs , which includes commentary on individual songs like a podcast... Continue reading… from The Verge - All Posts https://ift.tt/2Xz1oNc
Post a Comment
Read more

Instagram’s updated algorithm prioritizes original content instead of rip-offs

Image: Kristen Radtke / The Verge Instagram is making significant changes to how its system recommends content, with a focus on original content and increased distribution for smaller accounts. The slew of changes were announced by the company in a blog post today. The biggest change deals with aggregators — accounts that download or screenshot other users’ videos and photos and repost them. Sometimes aggregators will credit the original poster by tagging them in the post or caption, but often, content is wholesale ripped off with no acknowledgment, and engagement is siphoned off from the person who created the content in the first place. Instagram clearly has a problem with this and will begin removing reposted content from recommendations across the platform. The... Continue reading… from The Verge - All Posts https://ift.tt/ECgcPAU
Post a Comment
Read more

We asked camera companies why their RAW formats are all different and confusing

When you set up a new camera, or even go to take a picture on some smartphones, you’re presented with a key choice: JPG or RAW? JPGs are ready to post just about anywhere, while RAWs yield an unfinished file filled with extra data that allows for much richer post-processing. That option for a RAW file (and even the generic name, RAW) has been standardized across the camera industry — but despite that, the camera world has never actually settled on one standardized RAW format. Most cameras capture RAW files in proprietary formats, like Canon’s CR3, Nikon’s NEF, and Sony’s ARW. The result is a world of compatibility issues. Photo editing software needs to specifically support not just each manufacturer’s file type but also make changes for each new camera that shoots it. That creates pain for app developers and early camera adopters who want to know that their preferred software will just work. Adobe tried to solve this problem years ago with a universal RAW form...
Post a Comment
Read more