DeepSeek sees unprecedented success at the moment which is attracting the attention of everyone whether it is AI enthusiasts, cyberattackers, or stock market traders. The company is quickly becoming everyone's favorite app replacing the likes of ChatGPT, naturally leading to loads of traffic, performance slowdowns and other issues.
With all the buzz surrounding DeepSeek, Sam Altman, the CEO of OpenAI, has now responded to DeepSeek R1 calling it "impressive" and is welcoming the competition. Altman expects nothing short of AGI (Artificial General Intelligence) "and beyond". On his official X handle, he wrote:
deepseek's r1 is an impressive model, particularly around what they're able to deliver for the price. we will obviously deliver much better models and also it's legit invigorating to have a new competitor! we will pull up some releases.
but mostly we are excited to continue to execute on our research roadmap and believe more compute is more important now than ever before to succeed at our mission. the world is going to want to use a LOT of ai, and really be quite amazed by the next gen models coming.
look forward to bringing you all AGI and beyond.
Curiously, just about a week ago, Altman cooled down the AGI hype stating that it was still far off and that OpenAI was not going to "deploy AGI next month" and that it was not even "built" yet. Hence either AGI is still a long-term vision for the company or it is possible that the CEO of OpenAI did not want to give away too many details about its AGI project. He stated:
twitter hype is out of control again.
we are not gonna deploy AGI next month, nor have we built it.
we have some very cool stuff for you but pls chill and cut your expectations 100x!
Meanwhile, Nvidia has also responded to DeepSeek's success and this is particularly important given that more than $450 billion got wiped off its market value yesterday. In an email statement to CNBC, an Nvidia spokesperson said:
DeepSeek is an excellent AI advancement and a perfect example of Test Time Scaling. DeepSeek’s work illustrates how new models can be created using that technique, leveraging widely-available models and compute that is fully export control compliant.
Inference requires significant numbers of NVIDIA GPUs and high-performance networking. We now have three scaling laws: pre-training and post-training, which continue, and new test-time scaling.
Thus it looks like certain breeds of Nvidia GPUs were indeed used to power DeepSeek's software which should be good news for the hardware company as well as its investors. This should also be of some relief to Nvidia's competitors in the hardware space like AMD.
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