Jake

*very* few companies voluntarily involute their products. They bias toward upselling. At a minimum, they try to increase volume and keep ASP the same. "Raise prices for more functionality" has long been the norm. Lowering prices means "owning" a smaller pie, vs getting the largest absolute piece you can.

@JakeKAllDay @econcallum Why would you not pass the productivity gains to the customer and own the market? Prices should fall to the consumer, yet, they aren’t.

This is a highly underrated point. Programmer productivity improvements SHOULD show up as falling software prices. This is the historical norm. In fact, though, in recent months software prices have actually been *rising*...the opposite of what should happen

@econcallum it isn't -- this data is based on NIPA. It is an inflation (product) level metric. it has absolutely no way to scale for what features exist within a given software bundle. apps.bea.gov/iTable/?1921=u…

@JakeKAllDay Feature cost should be accounted for in this price index

@Goosehater123 @qcapital2020 'hard to disentangle' is a terrible excuse for misleading statistics. Amazon, by revenue, is mostly a retail company (not so by valuation). Measuring their AI capex, a tiny portion of their AWS business currently, against their retail revenue is dumb.

@JakeKAllDay @qcapital2020 Hard to disentangle. Machine learning has already been a core component of all their businesses. Just AMZ for ex. Amazon Ads, AMZ search, AWS, even AMZ logistics like FBA, warehousing, pick/fulfillment, etc. The line between ML and AI is hard to determine, It’s more gradual

Capex Bubble for ants

@qcapital2020 This is a crazy misleading chart. VAST majority of the revenue of Amazon/google/Meta/Oracle/MSFT has nothing to do with AI. Most of Amazon rev doesn’t even have to do with IT! Google + Meta are 0.5T in just Ad revenue. It’s apples and orangutans.

Pennsylvanians who want to buy recreational marijuana are already driving across the border to one of our neighboring states who’ve legalized it. That’s hundreds of millions in revenue going out of state instead of being spent here in Pennsylvania. It’s time for us to finally catch up — and for the legislature to send a bill to my desk and get this done.

MCP standard reached critical mass during 2.5/5/4 period and then the corpus existed to do proper RL for tool calling. Coding capabilities also progressed which was a tailwind on agentic scope. Gemini series is the smartest internally but their tool calling RL is still the weakest. Hence the disparity bw benchmark and lay engineer (I said what I said) perspective. Hopefully it gets fixed on the next cycle.

Extremely clear what caused the qualitative leap from GPT 4 to o1 (test time adaptation via chain of thought reasoning). Not clear what caused the agentic leap from Gemini 2.5/GPT 5.1/Opus 4.1 to Gemini 3/GPT 5.2/Opus 4.5. Even crazier all three released ~3 weeks apart.

@MichaelFKane One day, Children of Húrin will be made into a movie and Glaurung will get his due. @andyserkis already narrated it perfectly in audiobook form hopefully he can make that happen.

Arguably, Tolkien writes the Platonic Dragon, or as close as any story will ever get anyway.

@MichaelFKane “It’s only a REAL victory if there are zero detectable costs”

The US will never be allowed a military victory again because arbitrary metrics unrelated to actual military goals will be applied to declare defeat. And this isn't particularly a shot at Chris, because he is right that oil price standard will be applied to Iran, despite oil being a tertiary concern at best to the administration's actual objectives in Iran. But we are so well off and comfortable that talking heads will apply any discomfort or inconvenience to the account and credit it as a loss.

Moonshot AI continues to be the *most* open of the OS shops (#qwen and GLM are still great too!). #Kimi K2.6 is a legitimately frontier model, making it available from the start is great pressure on the Big 3 cloud providers to keep costs down. It should also be a boon to @cursor_ai users, as #Composer 2 was based on Kimi and provides vastly better value than Claude.

@ThePowerAudit I’ve never understood why people think Iran would seriously play the Red Sea card. It might not work, it will bring KSA into the fight, and will lose their CCP support. It’s great for Russia but that’s about it

The only cards Iran holds are a suicide card that assumes they can convince the Houthis to enact it too. I do not think they would at this point. I also do not think the US will eliminate the power plants in Iran. Game theory says you don't, not unless you want the destruction of the entire region as mentioned. (there is a devastatingly sad benefit for the US economically long term to this) China is not going to let the IRGC harm them and make them even more indebted to the US by doing it either. The "cards" Iran holds are not actually leverage. It is more of a threatened suicide vest strapped to the region. If I aim the US, I would NOT take out the power plants or attempt to send Iran to the stone age. But if Iran does pull the pin, guess whose oil and LNG just became the hottest commodity in the world? US LNG at $20 JKM. US propane at $1.13/gal delivered ARA. US crude exports at a record 5.2 million barrels a day. That is the position Iran's suicide card actually strengthens. Here is the game theory. Iran has two choices. Execute the threat and die, which makes US energy the strongest card on Earth and hands Trump the strongest hand in a generation. Or do not execute, and keep bleeding revenue through the filter every day the blockade operates. Both branches favor the US. There is no Iranian move that improves Iran's position. A threat where every outcome helps your opponent is not a threat. What sort of leverage is that?

@StirlingForge @Alibaba_Qwen It’ll be considerably larger (hence the naming convention). Just wait for 3.6 27B dense

@JakeKAllDay @Alibaba_Qwen I mean if it's like 122B like their last few big boys, then it might be feasible for me

🚀 Introducing Qwen3.6-Max-Preview, an early preview of our next flagship model Highlights： ⚡️ Improved agentic coding capability over Qwen3.6-Plus 📖 Stronger world knowledge and instruction following 🌍 Improved real-world agent and knowledge reliability performance Smarter, sharper, still evolving. More Qwen3.6 models to come. Stay tuned! 🔗👇 Blog: qwen.ai/blog?id=qwen3.… Qwen Studio: chat.qwen.ai/?models=qwen3.… API: modelstudio.console.alibabacloud.com/ap-southeast-1…

@StirlingForge @Alibaba_Qwen Too many for you to worry about running it locally.

@Alibaba_Qwen OPEN SOURCE IT PLEASEEEE. Also how many parameters is that?

@IrvingSwisher Gasoline prices were 4.4% of GDP at the peak of the 1980 shock. They’re typically less than 2% in today’s economy. Oil as a % of US energy consumed is vastly lower than it was before. Brent prices also =/= broader petroleum costs. open.substack.com/pub/jakekooker…

This would be good for an interview question to test basic statistical reasoning “How valid is this claim based on this chart?” “What else would you need to know to feel confident making this claim” [It is a dumb slide that misses the relevance of petroleum products to growth]

@VKMacro @stja42860 China is hoarding oil and has banned exports so it is logical to treat them as a separate, dislocated market.

@stja42860 Not a different conclusion per se, but China inventories have been flat to up since the crisis began. Also, China demand can fluctuate significantly in the near term which offsets against RoW inventories.

Sorry but you have to include China lol

#gemini has shown the last few months that as long as you’re near the frontier, the most important thing is reducing cost to serve (through MoE, vertical integration/TPUs, etc). Worth noting Google has added more this past year than oAI + Anthropic are worth combined ($2.3T!)

Worthless? No (try fine/many liberal arts) But, SWE roles for a long time did command a major premium vs other IT roles like sys admin. That premium is going to compress due to coding agents, at least at the entry level. But there is also initial data suggesting a rebound in SWE hiring, with new roles created at companies that historically didn’t hire any/as many as major tech firms.

@JakeKAllDay @cloneofsimo Like computer science?

We are *already* seeing massive tech job hits due to AI. Like jobs dont magically appear, they appear when there is *increase in demand* or *decrease in supply*. You have to be absolutely blind to not feel this: lot of fresh graduates are struggling to get a job in tech. Its completely wishful thinking that AI will create more jobs. Nobody promised that, and current trend (maybe only empirical evidence we have) certainly dont back it up.

I don’t really understand this objection, I’d like to hear more about it. The original paper also looks at OOLONG-pairs which is significantly more complex than NIAH. We have implemented harnesses that are conditional versions of RLM (not worth it below ~40k tokens). And selective context loading is extremely well proved out by cursor, even if it isn’t as aggressively context-scarce by default as RLMs aim to be

I've been looking at RLMs lately, I'd say I'm shocked that the people boosting them on my TL can't spot the obvious problem for trying to apply them to the vast space of large-context inference scenarios that'll never ever fit the needle-in-a-haystack paradigm, but I'm not.