291–300 of 315 posts
> Like, imagine if some serious business leader, like, idk, Mark Zuckerberg, decided to announce that Meta was going to burn money. Like ... pivoting to the "metaverse" and changing the company name to show he's serious.
It's astounding to me that they looked at Second Life and really thought that was the future.
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It seems really absurd that anyone would encourage or even force employees to burn more money to see if maybe something works.
Why? This is literally what experimentation and prototyping is ! You spend money for a potential benefit. In this case it’s also a one off cost to find things that can save money over time.
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You don't need peer reviewed studies to tell you water is wet. Peer review is a technique to get evidence from data when SNR is low. It's not "science", it's just a technique. So is "throwing shit at a wall and seeing what sticks". Don't turn techniques into rituals, and science into religion.
> You don't need peer reviewed studies to tell you water is wet. I'm afraid I have bad news for you...
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> Plenty of people are critical of AI at my job despite a big push to use it. Are they critical to you and your 10 people team, aka a small circle or are they critical in the all hands Q&A in front of 500 employees?
Having been the guy to speak the uncomfortable truths at such meetings, I can tell you that does not end well for anyone. Expect to look for another job shortly afterwards.
Folks have been saying “things are different now, the agents are now compounding success instead of error” for at least a year now, but I just don’t see it. I was lucky enough to receive a weeklong $50k per head AI training from the people saying these things, and one of their few helpful concrete recommendations was to constantly clear context all the time, to avoid things going off the rails. However, I think findi…
It's true, but I see it happening. I’ve watched seniors with 30+ years of experience adopt them successfully without losing their classic rigor. Personally, I get huge mileage out of LLMs, and yes, I care deeply about code quality, readability, and debuggability. I've seen juniors absolutely rock with them. And I've seen the exact opposite, where they just struggle to get good results. In the end, I think the divide…
Folks have been saying “things are different now, the agents are now compounding success instead of error” for at least a year now, but I just don’t see it. I was lucky enough to receive a weeklong $50k per head AI training from the people saying these things, and one of their few helpful concrete recommendations was to constantly clear context all the time, to avoid things going off the rails. However, I think findi…
In Hawaii I assume?
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To use your analogy again, it's kind of like the shop boss buying everyone a table saw and then saying "The best way to use the table saw is just experiment with it, it's the fastest and most accurate straight cut we can get - the future is table saw."
Yes, this is, in fact, how adoption of table saws and other such tools looked like, while they were still new tools. The basic form and function was established and its utility proven in both testing and early adopters, but as new kind of general tool on the market, every user from "early majority" was still writing the operating playbook for their specific shop conditions and kind of work they're doing. So yes, it's…
See, table saws are dangerous. Famously so. One of, if not the most dangerous tools available to the general public. They spin quickly with lots of torque and pull things in faster than you can react. Pressure can also send loose pieces of wood backwards at high speed. Fast enough to pass through a person sometimes. It's like being hit with an arrow.
Tablesaw accidents can remove fingers and hands instantly, puncture organs.
They can be used safely but they're circumstantial, the worst thing you can do with a table saw is experiment. Once you realise there's a 12-inch razor sharp blade spinning at 3000rpm with up to 5HP you begin to respect how dangerous it could be and want to warn others.
It's intentionally hyperbolic. But you see what I'm saying here?
Earlier quoted context omitted.
Yes, this is, in fact, how adoption of table saws and other such tools looked like, while they were still new tools. The basic form and function was established and its utility proven in both testing and early adopters, but as new kind of general tool on the market, every user from "early majority" was still writing the operating playbook for their specific shop conditions and kind of work they're doing. So yes, it's…
No, that's not what this analogy is about. At all. See, table saws are dangerous. Famously so. One of, if not the most dangerous tools available to the general public. They spin quickly with lots of torque and pull things in faster than you can react. Pressure can also send loose pieces of wood backwards at high speed. Fast enough to pass through a person sometimes. It's like being hit with an arrow. Tablesaw acciden…
And yet, that's very much exactly what happened, well predating the table saw; look into steam engines belt driving saw pit blades for logging.
The table saw itself has evolved in many ways, there's a handheld angle grinder with various blades sub tree.
These attachments: https://www.arbortechtools.com/au/shop-online/power-carving/...
are the literal evolution of wrapping chainsaw about discs on an angle grinder: https://www.afr.com/companies/an-inventor-cuts-in-big-time-p...
It's hard to be hyperbolic about danger and spinning objects, blades, chains after looking into the crazy world of farmers and military civil engineers; a shed built whipper snipper for young trees in a plantation to clean rows made out of chains welded to a tractor rim spinning horizontally hanging down behind rig on small tractor and driven by the PTO is not the scariest thing I've seen.
Long story short, people using tools often make and evolve their own tools to better do their work - and sometimes iterations of those proto-tools are kinda super bloody sketchy. There is care to be taken, there will be close calls.
> That’s no longer true. We’ve entered a different regime, where spending more tokens generally results in better results. We call this “compounding correctness” — the more tokens you spend on getting a task correct, the more likely you’ll get a good outcome. We talked about this a bit at the last in person Agentics meetup: Have we? Is it generally the case that the more tokens you spend, you better results you get?…
Looks like it based on Anthropic’s own multi-agent orchestration research: https://www.anthropic.com/engineering/multi-agent-research-s... Their findings suggest multi-agent systems result in better performance attributed mostly to token usage (80% of variance).