Morgan Stanley Reaffirms ‘Overweight’ Amid AI Growth and Political Tailwinds from Trump Administration


We recently compiled a list of the 15 AI News That Broke The Internet. In this article, we are going to take a look at where Tesla, Inc. (NASDAQ:TSLA) stands against the other AI stocks that broke the Internet.

One conversation gaining traction in Silicon Valley these days is how the advancement of Generative AI models is slowing down. Deirdre Bosa takes a look at the matter in CNBC’s TechCheck, revealing how rapid genAI advancements are now showing signs of deceleration. She notes how the quality of improvement in OpenAI’s upcoming model, Orion, is expected to be smaller than the leap from ChatGPT-3 to ChatGPT-4. This smaller advancement is largely due to a limited supply of training data, a key factor that could significantly affect how investors view AI companies.

READ ALSO: 15 AI News That Should Not Be Ignored and 10 Trending AI Stocks on Latest Analyst Ratings and News 

Nevertheless, OpenAI CEO Sam Altman has boasted on X that ChatGPT is now the eighth-biggest website in the world by traffic. As of October, ChatGPT had 3.7 billion visits, versus Perplexity’s 91 million visits, and Google Gemini’s 292 million visits. Nevertheless, the plateau in technology advancement doesn’t necessarily mean a slowdown. For instance, Mark Zuckerberg proposes that there is a lot of opportunity to build consumer enterprise applications on top of the existing technology.

While that is certainly an option, Reuters has reported that artificial intelligence companies are seeking a new path to smarter AI due to the plateau. Ilya Sutskever, co-founder of AI labs Safe Superintelligence (SSI) and OpenAI, told Reuters recently that scaling up pre-training for AI models, which involves using large amounts of unlabeled data to learn language patterns, has reached a plateau.

“The 2010s were the age of scaling, now we’re back in the age of wonder and discovery once again. Everyone is looking for the next thing. Scaling the right thing matters more now than ever”.

In light of this, researchers are now looking at a technique called “time testing compute” for improving models during the “inference” phase when such models are being used. The technique will allow the model to test different options instead of giving a single answer. The implications of the technique are far-fetched, having the potential to change the competitive landscape for AI hardware.

Fortune predicts that GenAI funding is going to decelerate this year. However, it also believes that the industry’s recent breakthroughs are among the most profound technological advancements of our time. Regardless of the slowdown in GenAI models, artificial intelligence continues to be a breakthrough in many industries today.



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