Maybe I'm wrong, but I feel like creating device tree should be relatively straightforward if driver support is there. So while having official device tree is awesome, it's not something that's very hard to do. Now writing drivers without datasheets, using reverse-engineering is something that's hard to do.
I've been waiting for someone to write a DTS for a Snapdragon(R) X - X126100 - Qualcomm(R) Oryon(TM) CPU based laptop I bought over a year ago. Some people are trying but it can't be that easy ... Starting to look into doing it myself and AFAICT it requires reading the ACPI tables (written for Windows drivers), and manually converting it to devicetree, test, tweak, repeat.
They accept Object not because they're not type safe. They accept Object because key `equals` method might return `true` for unrelated classes by design, and collections interfaces have to accommodate for that. In other words, you might put key of class C1 into the map, and later use `get` with key of class C2. And if these classes happen to implement `equals` accepting each other, the collections are supposed to work.
So the core issue is that `Object.equals` method isn't type safe. Collections API just follow that.
Cyber attacks between these countries were happening on large scale since the beginning of the war. There were several huge breaches, but otherwise most high-profile companies adapted and significantly strengthened their protections. Rest assured, you can be sure that both sides right now utilize available AI both for attack and defense.
You don't need data center for inference. Even largest models run on a single server. You need data center for training; or for serving millions of users. Evaluating the model is neither of those.
If you need, you can trivially backport the code to JDK 11. All new Java features are essentially syntax sugar and trivial to rewrite with early Java code. Just ask LLM, they're really good and mundane and trivial rewrites.
He may be hinting that solving these complex mathematical problems will boost OpenAI clients' confidence and encourage them to spend millions of dollars on solving other complex problems.
I would think it would have the exact opposite effect.
Why would anyone use OpenAI models for anything commercially valuable, or where secrecy is important, when it appears that if OpenAI "becomes aware" that you are doing so they may try to compete with you?
Not only did OpenAI, by their own admission, rush to re-solve Navier-Stokes once they heard the rumor that it has been solved (the rumor being that it was Anthropic that had done it), but they are leaving the door open ("we cannot rule out that") as to whether the model they used to do it had been trained on the anonymized date from the researchers who's approach they ended up copying.
Terrance Tao has recently said as much for mathematics - that there appears to be a trend (not just this Navier-Stokes incident) of the AI companies going after math problems wherever there is an "rumor" of progress, and that he thinks this may sadly result in breakthrough mathematics being conducted in secret to avoid this.
The rush to steal another researcher's thunder is bad enough, but it also appears that one of OpenAI's employees acted in a very thuggish manner to try to threaten the professor who had been working on this not to publish and to co-operate with their telling of the story.
>but they are leaving the door open ("we cannot rule out that") as to whether the model they used to do it had been trained on the anonymized date from the researchers who's approach they ended up copying.
This is just lawyer speak. Maybe there was a small reward from a possible thumbs up on any of the chat sessions. Open AI have no way of knowing if that happened or not and the chances that, if this did happen, that it had anything to do with their solution of Navier Stokes is extremely unlikely.
>to try to threaten the professor who had been working on this not to publish and to co-operate with their telling of the story.
There was never a threat to not publish their own work with whatever credit to whoever. This was about the offer to be a lead author on the paper that Open AI authored, an invitation that was not extended to Levant.
Yes they know the timelines, which they've explained. No they don't know exactly what they train on. Even I don't, and my little experiments are nowhere near OpenAI scale. This is par the course for ML. Plus it would kind of defeat the purpose of de-anonimization if they could.
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