xuancanh

They list Anthropic as one of their customers and appear to have conducted penetration testing for them previously, so they're likely one of those trusted organizations.

Meta did exactly that, kept him but reduced his scope. Did the broader research community benefit from his research? Absolutely. But did Meta achieve a good outcome? Probably not.

If you follow LeCun on social media, you can see that the way FAIR’s results are assessed is very narrow-minded and still follows the academic mindset. He mentioned that his research is evaluated by: "Research evaluation is a difficult task because the product impact may occur years (sometimes decades) after the work. For that reason, evaluation must often rely on the collective opinion of the research community through proxies such as publications, citations, invited talks, awards, etc."

But as an industry researcher, he should know how his research fits with the company vision and be able to assess that easily. If the company's vision is to be the leader in AI, then as of now, he seems to have failed that objective, even though he has been at Meta for more than 10 years.

In industry research, someone in a chief position like LeCun should know how to balance long-term research with short-term projects. However, for whatever reason, he consistently shows hostility toward LLMs and engineering projects, even though Llama and PyTorch are two of the most influential projects from Meta AI. His attitude doesn’t really match what is expected from a Chief position at a product company like Facebook. When Llama 4 got criticized, he distanced himself from the project, stating that he only leads FAIR and that the project falls under a different organization. That kind of attitude doesn’t seem suitable for the face of AI at the company. It's not a surprise that Zuck tried to demote him.

My guess is from the customer's perspective, DSQL seems to have too many limitations, making it feel more like an enhanced version of a NoSQL database with SQL semantics, ACID transactions, and multi-region capabilities rather than a truly distributed version of a relational database. It seems the DSQL team doesn't fully understand why relational databases remain widely popular today. What makes them great is their flexibility, which lets them handle all kinds of use cases and adapt as things change. But all the limits on transaction size, column size, etc.., and too many missing capabilities pretty much take away all the big advantages relational databases usually offer.

The limit is for query operations, not just transactions.

AWS tends to prioritize performance and scalability over functionality, which is reflected in the design of DynamoDB, SimpleDB, and now DSQL. I'm also not a big fan of this style. It doesn't give customers the flexibility to choose their own trade-offs like Spanner does and assumes that customers can't make these kinds of decisions on their own.