I really don't see any conclusions which would be such a game changer and critical, that this information has to be perfect.
And its Version 1 and an ongoing project.
"In the workplace, we show that while AI adoption spans
occupations covering just above 88% of US employment, penetration remains shallow and
overwhelmingly collaborative in nature, with end-to-end task automation limited in scope.
Outside of work, AI spans activities making up about 98% of Americans’ non-sleep time,
with disproportionately high use in high-friction tasks such as engaging with government
and professional service providers, likely delivering economic value that standard national
accounts may miss. Globally, adoption scales with national wealth and has broad linguistic
distribution, with English queries representing only around a third of volume."
It sounds reasonable enough and it contains nothing off.
For me its interesting to read that english is less dominant and thats def something i was very atuned when GPT-3 came out: I started to write english and my native language and mixing up words etc. The quality of understanding in my native language is sledomly good when a new product comes out but it was very good already when using GPT-3.
In comparision to this, i'm also aware of a research paper stating that programming in certain languages like spanish is worse.
I read somewhere that the memory companies were massivly pushed for lowest prices especially by companies like apple.
I want to hope that this money will lead to more capacity, more R&D and lower prices in the long term again.
Nvidia would have changed its GPU strategy a long time ago if the demand wouldn't be real. They still can afford the GPU prices. But memory is not a monopoly.
For memory though i do assume a lot more people and companies want a massive amount more memory than ever before. I have 64gb in my pc for a few years now, i was quite happy with that. It became a no brainer. But today? Hey give me 100, 300 and even more. I really want to run bigger LLM models locally.
Yes that is unfortunate for sure don't get me wrong this affects me but the overall benefit will still be bigger i assume.
10 years ago i watched a talk about the problem of compute vs. memory. Compute increased significantly while memory speed did not.
This gigantic investment will solve this problem.
So either this blows and we will have way too much capacity which will lead to cheap and mass amount of memory for everyone + cheap GPUs again OR AGI. So win - win.
We haven't even started with a lot of things were we need a lot more compute:
Your real personal agent which knows you and helps you like "good morning elmer2, your calendar invite for dinner is today, you will need to leave at 18:18 if you want to use your normal public transport route per train. I put an alarm in your phone for you"
Agents to agents
Agentic teams.
Finetuned models for everything like Java/spanish coding model.
Very long term research like multiply hours or days or weeks and plenty of these in parallel.
If they continue investing in compute, memory, memory bandwidth, network infrastructure, etc. it makes a relevant contribution of progress in all of these fields which I will leverage.
A small form factor PC with 100gb fast memory and being able to run something like sonnet or opus level LLM would be massive.
I have so many things i want to do and still sitting it out due to cost.
I'm lost. If you referene Noam Shazeer in context of Character.ai vs. Ragdoll Studio, Noam Shazeer and all other co-authors have done the work for Attention is all you need while working for/at Google.
They are for sure one of the current Frontier AI labs.
And before their competitors and china started to be that fast, they were regularly publishing a lot of research in this area too.
Of course a company is not unbiased. I don't blindly just take the information of an article, i add it to my signals and evaluate it.
But the dismissivness of a normal / small blog post is weird. You can't just complelty ignore and dismiss one of the biggest companies on the planet who is also one which pushes research of it too (aka deepmind)
2. They do have gemini which I don't use for coding but I use daily for other things, it works well. They have massive data center capacity, that they are now renting space from SpaceX shows how big the demand is.
3. yes weirdly enough but doesn't matter too much, Google at least can just afford the investment in comparision to any other company playing that game. My assumption is that on one side google is just bad in releasing products (antigravity vs. gemini cli vs. unable to buy AI tokens as a normal user etc.) but also that they might just have a broader field were they want to use AI.
Claude/Anthropic can focus on coding a lot to push that frontier while google might focus more on gemini assistent and also for coding and using gemini for GCP etc.
But doesn't matter still, google was fundamental for research into LLMs.
4. No clue how this is a problem relevant to the AI Economy. Deepmind might be more independent from Google itself, Google has an internal AI coding system before the LLM stuff became popular so Google has a clear incentive of keeping the feedback loop internal. Independent of this, google is well known to control their whole ecosystem starting from the mainboard firmware. Im not even aware of any other company on the planet doing it like this.
For me its valuable enough to have a quick look. I would probably not have posted it on HN or voted up.
I'm more surprised about the generic negative sentiments people communicate here instead of having nice discussions with value.
My company i work for is real, normal big global company.
Not sure if its really top 100 or top 150, I checked google and the lists again i can find it in one i can't find it in the top 100 in the other. Shouldn't matter though the 2 digit billion dollar revenue is true and the amount spend on tokens is true too.
Everyone has access to claude, we get reminded regulalry to invest time into using AI.
I never seen google blog articles as something millions of people read. For me these are small lenses in a big company were i pull out small details i might find interesting.
Im missing the marketing opportunity here.
The spending is a complete different topic though. Google/ABC can easily afford their investments. Microsoft and Amazon too. Even if shareholders are not that happy (the shareprice of alphabet doesn't tell this story though) with it.
Nonetheless the biggest issue with this spending are 401k and other retirement investments from people who can't control the investment and the undefined risk of it. Thats the only real 'risk' (not a small one for these people depending on it though).
It doesn't affect me if Google spends its money on AI.
Nonetheless the progress on AI is huge, it still hasn't slowed down, its now a political and global issue (us export restrictions, Chinas Moonshot AI/Deepseek, EU lagging behind).
At least form my point of view, i'm very surprised that we even risk all of this investment and see it as a possitive thing. Imagine AI/AGI is a technology which sits very far away from our current local minimum and the jump to the other local minimum is massivly expensive but massivly beneficial?
GPT-2/3 was able to inflict this vision into people and because of this, we get A LOT more compute, push again boundaries on compute and memory after a longer period of stagnation. These richest companies in the world like Google also leverage the AI spend into investment of fusion and other energy sources.
We already got a lot better vision ML algorithm because of this (tx to suckerbergs dino and segment anything), we have alphafold tx to Googles Deepmind etc.
AI only consumes currently a little bit more about bitcoin but is acutally beneficial.
Its still crazy how much energy bitcoin wastes, how much energy bitcoin steals.
Ironic enough, if you know wwere a bitcoin millionar is, its a lot easier to steal from them too.