For example MSFT (not a small player i know) is having its slightly different approach to those signals and they cannot be used here (search scitt). I mean different type signature envelopes, different roots of trust. But in the spirit it is the same. This approach is partially a territorial grab by google (first npm, then pypi, next golang). But importantly I think these security improvements are marginal and you are at the mercy of the dependency developer anyway. Just look at npm, they had some nasty vectors and similar “improvements” were close to useless in those cases.
It is a valid assumption but I would have expected the article to provide such details. And why would you not want to hire a socially awkward person, if I do that for my business I just want results and awkwardness doesn’t matter much in technical positions.
Have you ever tried to hire such a person? I can guarantee you it is not as easy as you might think to get something useful out of them. Normal smart people simply can't deal with others who have severe Asperger's (or any Autism spectrum disorder for that matter). The only place I could see for those people is in a back room in some university where they get to research whatever they want with no teaching duty. But these positions are ultra-rare and you basically have to be super accomplished before you are even considered.
There are other cases, and it can be very valuable to be able to get something out of someone with a lot of technical ability but poor collaboration, but I do agree it's something that will reduce their value to most employers substantially.
Like what? And how do you get something that you want out of somebody who doesn't care or understand what you want? He may see you like a fat gorilla asking Einstein to fetch more bananas. Or maybe you can't even hold his attention long enough to formulate your desires. Most people have never interacted with this kind of Autism. In any result oriented environment where the results are governed by others, this person is essentially worthless to you.
The article does not talk about numbers. It is hard to understand competition in the field he is applying to. Then having the opinions of his parents does not help, it’s odd I need his mom telling me the CV looks good. It would have been better to question Princeton here as it is in their interest to make sure alumni get the jobs. It would be useful to ask some recruiters about the possible red flags for this guy, just to be sure. In any case sure I understand and sympathise, anyone would be mentally broken after that many job applications.
You could ask the agent to attempt to recover using specific tools. But yes in some cases the bits could be lost without the ability to recover, there are ways to destroyy data as it is usually required for decommissioning
It all sounds good and he is on the right track but the elephant is not that. The problem is that ordinary businesses do not see ROI from dumping cash on this direction. If someone wanted to have similar access to models as internal folks in these companies, then you’d need a bit of cash to run such swarms of agents, not to mention people who would know how to do it. Another thing is that you’d need your own frontier models deployed in the place where the inputs would not be exposed to a third party, as it is important to feed the internal private info to reason about. And if you are like me then it is a constraint of capital and people who want to invest in you that is also a factor, why would they invest in you when openai/anthropic will be able to copy your ideas in a few months?
the question is how much of this inability to realise roi is technology vs skill. i have plenty of clients who drop 10m on an enterprise transformation project but couldnt (currently) manage the power a 10m nvidia rack would give them, its only a matter of time before they can or their competitors can.
The economics part is the one I feel the biggest disconnect in the Tweet.
If teams had the same level of access as the "top 5000", you'd see different use cases proliferate. Same as we see an explosion in productivity when we advanced public education (more people can read, more people can contribute, more talent is discovered), same as we see an explosion in creativity when we advance distribution (from 3 broadcast channels to cable to streaming), same as we see gains in athletics with population size and diversity.
A lot of SAAS is easy to duplicate but not a lot of it is. The barrier is market/mind share. Something like Slack is easy enough to duplicate that many companies did. But everyone still uses Slack because that's what everyone is familiar with.
Just to sprinkle more details here about MSFT. The usage was trimmed down even more for some orgs and some specific accounts (I think those were vendors and the like). But if you are an FTE and somewhere in CoreAndAI then your limit is like 1M GitHub credits ($10k as article mentions) that could be spent on any model you have access to, e.g. Opus 5x or GPT-x. It is hard to pin down how many people use Claude vs how many just use internal harness over the Opus though. Importantly, Anthropic models are more expensive (not even talking about Fable here as it is a special case) as seen in usage metrics. Peeps can check their usage which has a good breakdown that shows how many tokens were burned on which model and how much that "costs" (the prices as you can imagine are not consumer ones), so IMO this change will drive more people to optimize based on their usage patterns if they are heavy hitters. The easiest path is to just switch to something like Sol/Astra and have similar perf for lower price.
> Peeps can check their usage which has a good breakdown
Must be nice. At Sony we use Copilot (as an MS enterprise customer) and restrictions to token usage circa June have resulted in a hunger games of who-can-use-them-all-first, with the pool usually drying up by the 10th day of each month.
As for usage breakdown: we got a manually-published table most days just showing per-user token usage, until eventually we were told even that was somehow too difficult to provide.
Between that and learning how much the whole of Sony Corporate Group spends on Copilot (spoiler: it's hilariously little), I've sort of run out of disbelief.
I'm so glad I work at a company that isn't looking at our token usage. I mean, we're encouraged to use it but hearing about leaderboards and things is wild - but we also aren't big enough to need API costs, so power users get a flat rate 200/Month subscription or whatever.
I could see finance looking at it from a cost perspective if it was API costs, but sharing it with the rest of the users feels like a different measurement...
To clarify: we don't have leaderboards (thankfully), our issue is more in the opposite direction, with people who do want to make use of the tools (optimally or not) majorly constricted from doing so.
> I could see finance looking at it from a cost perspective if it was API costs, but sharing it with the rest of the users feels like a different measurement...
It is indeed surreal. I am not bullish about this company's technological capabilities going forward tbh.
The fear-and-loathing generated by those colleagues who no longer can or want to synthesize anything themselves after the token-fueled high does indeed make for good popcorn viewing.
> Importantly, Anthropic models are more expensive (not even talking about Fable here as it is a special case) as seen in usage metrics.
Not sure where you see that. The API prices of Opus are cheaper than Astra and there was a study suggesting that the Anthropic abos are offering more bang for the buck:
From what I could see these numbers would usually be hit by people doing vast amounts of analysis over files, they would usually rock up tokens very fast. Then you combine this with the selection of Opus models which are much more expensive internally than GPT ones and the limit gets reached quite quickly.
I think it is important what they mentioned about using languages as well. Some smaller nations think they will culturally vanish because their “heritage” is close to nonexistent in the training data. If Mistral uses more of that language specific data it is a good thing and might help selling it to different non-english groups.
There was a section showing malware analysis which is great to have. I suspect everyone is using Chinese for this nowadays but now you can switch to this as well. Opus like GPT are restricted, it is hard to work with them doing offensive security and Fable is expensive.
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