pbmango

This is fascinating as a lover of both oil painting and history.

I can't help but think of Iphone updates since about 2018. The thinnest, fastest, longest battery life Iphone ever. It seems mostly the same and I probably won't be able to tell other than the name, but everyone buys it anyway.

This is good psychology for the labs. When Buffett invested in Apple he loved citing how most people would rather give up their second car than their Iphone.

Anthropic is getting capacity from Colossus 1 not Colossus 2 it sounded like. The initial colossus capex was under $5B, making that an even more astounding payoff.

Edit: S1 states both are being leased so the 20-25B initial investment probably more relevant

I imagine a huge proportion of their users are under 30. The prompt examples included even use the tell tale all lowercase (though apparently sama types like this too).

This is probably less pandering to genz and more speaking their users language.

This is very interesting. I don't see much discussion of interpretability in day to the day discourse of AI builders. I wonder if everyone assumes it to either be solved, or to be too out of reach to bother stopping and thinking about.

Along these same lines, I have been trying to become better at knowing when my work could benefit from reversion to the "boring" and general mean and when outsourcing thought or planning would cause a reversion to the mean (downwards).

This echos the comments here about enjoying not writing boilerplate. The there is that our minds are programmed to offload work when we can and redirecting all the saved boilerplate to going even deeper on parts of the problem that benefit from original hard thinking is rare. It is much easier to get sucked into creating more boilerplate, and all the gamification of Claude code and incentives of service providers increase this.

As the founder of another product in this space - this is super impressive and well built. Great demo video and congrats on top of HN! Getting this smooth UX and data behind the scenes is not easy.

> Whether intentional or not

I am not claiming it was intentional, but it certainly magnified the media attention. Maybe luck and not 4d chess.

It is also possible that this "world view tuning" may have just been the manifestation of how these models gained public attention. Whether intentional or not, seeing the Tiananmen Square reposts across all social feeds may have done more to spread awareness of these models technical merits than the technical merits themselves would have. This is certainly true for how consumers learned about free Deepseek and fit perfectly into how new AI releases are turned into high click through social media posts.

There are probably many more small battles being fought or emerging. I think voice and PDF parsing are growing battles too.

I think an under appreciated reality is that all of the large AI labs and OpenAI in particular are fighting multiple market battles at once. This is coming across in both the number of products and the packaging.

1, to win consumer growth they have continued to benefit on hyper viral moments, lately that was was image generation in 4o, which likely was technically possible a long time before launched. 2, for enterprise workloads and large API use, they seem to have focused less lately but the pricing of 4.1 is clearly an answer to Gemini which has been winning on ultra high volume and consistency. 3, for full frontier benchmarks they pushed out 4.5 to stay SOTA and attract the best researchers. 4, on top of all they they had to, and did, quickly answer the reasoning promise and DeepSeek threat with faster and cheaper o models.

They are still winning many of these battles but history highlights how hard multi front warfare is, at least for teams of humans.

Growing up in Buffalo New York, I only once as a kid saw one flying while on a camping trip in a remote state park. Now, you see one almost every day on the coastline of lake Erie. They are so much bigger than other birds that you will notice even if you are not on the lookout. Their scale is astounding compared to sea gulls.

They have also come back to the Potomac and Washington DC which is nice.

Great demo! Going to try this with a huge folder of call recordings that I would love to search across. Does it work with Google Docs as well as PDF?

Congrats! Big fan of Fig and excited to see the UX brought to aws CLIs

Interesting. I think a lot of AI agent internet navigation is still being figured out. Both rules as implied in comments but also tools. There are a lot of nuances OpenAI probably doesn't want to dedicate too many cycles or open up risk for.

Folks at Perplexity AI are doing a great job for general info AI charged browsing that's comparable to Bard. Our startup Promptloop has a web browser model targeted specifically at market research and business research. There are certainly many different ways to connect internet and model.

Great demo video - I like the focus on being open an flexible, knowing how much will change in the next year.

This is very cool and could be the basis for a huge set of interesting operations - but any time I read about DB <> Spreadsheet discussions they seem to be started by folks who much better understand DBs.

The principle use of the spreadsheet for both power users and casual users is a lot around justifying answers by being able to see the data. The goal is not speed or scale.

If you and sending a report to a superior - clear and visible rows, columns, and "math" makes it faster and easier to trust information for non-technical users.

This same logic is why the spreadsheet is best serving customized, one-off, or changing operations without a huge amount of data. This makes up a huge chunk of day-to-day business decisions, especially in finance where the math is much easier.

I don't think the spreadsheet lasts forever, but its successor will likely be something that presents an easy way to get answers from a set of data that is visible or at least able to be quickly understood, regardless of whether its fast, scalable, networked etc.

This is great. Can endorse LuckGrib for IoS folks as well. Great UI and can pull NOAA and EU models. https://luckgrib.com/. Not FOSS but worth the $20 I paid once several years ago. Popular among wind sports enthusiasts many of who are hobbyist meteorologists.

Yes - Not open access yet but drop me an email!

Microsoft and Google both have excellent formulas for dates - and are getting there for addresses. Right now - the most useful things you can accomplish in sheets center around what the underlying models are good at - general inference and generation based on text. Anything needing exact outputs should be a numeric formula or programmatic.

Non-exact outputs are actually a feature and not a bug for other use cases - but this takes a bit of use to really see.

There is a huge potential for language models to get close to messy text problems (many of which are in Excel and Sheet). I am the founder of promptloop.com - the author of this tweet has been an early user.

The challenge to making something like this, or Co-pilot / Ghostwrite, work well is about meeting users where they are. Spreadsheet users dont want to deal with API keys or know what temperature is - but anyone (like this tweet) can set up direct API use with generic models in 10 minutes. This document has all the code to do so ;). [1]

For non-engineers - or folks who need a reliable and familiar syntax to use at scale and across their org - promptloop [2] is the best way to do that. All comments in here are great though. We have been live with users since the summer - no waitlist. And as a note - despite the name "prompt engineering" has almost nothing to do with making this work at scale.

[1] https://docs.google.com/spreadsheets/d/1lSpiz2dIswCXGIQfE69d... [2] https://www.promptloop.com/

This looks extremely crowded - but reminds me of how apparently hard it was to find or bump into another ship crossing even a confined sea like the Med before sonar. With three dimensions here and more avoidance planning, even this level of space probably looks very empty still.

If you take two obvious leaders in manufacturing excellence (for this audience at least), Apple and Tesla, they both now in 2022 seem to be running up against repair and service problems. Part of this might be that they have so optimized the rest of the funnel that these blotches stand out in even more contrast. When the goods are cheap, late, or defective their lack of post-purchase service is taken for granted.

I think most of Bridge's barrier to entry is perception. Before I learned the basics and started playing with friends and family I had the understanding it was extremely complex, on the order of playing a new instrument. This turned out to not be the case and anyone with a basic grasp of cards, probability, and betting can figure it out.

There is also the social perception that is a game older people play, specifically older women. Without fail when I suggest a game or someone to learn it they reference "Its what my grandma plays". This is driven more by just how popular cards used to be, bridge one of the most popular. Something on the order of 3 of 4 were in a regular card playing group mid century I remember reading. As that population retained the habit the average age of bridge player is now in their 70s whereas it used to be much lower.

This conversation is especially interesting given the FDIC is probably the most decentralized component of traditional financial infrastructure.

It has cost taxpayers effectively nothing and rests on mutual insurance across the system. Yes there is a line of credit to the Treasury but the overall security it has provided for 70 years is probably hard to measure compared to the Fed buying/selling activity. I know there are probably teams working on this for crypto already (without the law mandate).

I get that. And we read horizontally. But why do we still align text in vertical blocks like print pages for consumption. Just idle musing here.