Either you are getting the smartest engineers, or offer the most freedom to pursue interesting goals that aren't on the frontier. Amazon has neither so they naturally aren't going anywhere in that domain.
Your comment was likely focused on dysfunctional parts of the culture there (and that seems to be how most replies to you interpreted it as well). There's truth to that, sure. But I think respect for data sensitivity and security is also a big part of what makes the culture ill-suited for frontier AI lab work.
When I was at AWS, we had data access locked down very tightly. I was trying to train a model to predict how long various dynamic workloads running on behalf of customers would take. Just getting access to anonymized production data from a DB that my team owned took well over a month and had me compromise heavily on what attributes I could access. I also spent a decent amount of time in meetings with lawyers and compliance folks to explain and justify all our data classifications for PII, retention, access controls, etc. We would review our data policies quite frequently. We needed break-glass procedures to access prod data in our own systems, and it was uncommon to need to resort to that. Even when you broke glass, certain classes of sensitive data would still not be visible to you. On the plus side, We did get quite good at operating and maintaining systems without needing to see sensitive info.
If you contrast that with Meta's disregard for privacy or the way frontier labs disregard the law, it's easy to see why Amazon would struggle in this space.
I read your comment as “amazon acts too responsibly to be a frontier lab,” and that worries me. That they even bothered to do all that stuff is good. That others don’t is bad.
I did indeed mean it that way, but I agree with you. It sucks, but it's just the unfortunate reality of the world. Many of the most disruptive and successful startups made it there by ignoring legal or moral limitations.
That explains a lot. They are anti “move fast and break things” which is great news for enterprises or anyone seeking stability but terrible for innovation.
I don’t condone the use of pirated content for training. But anything that was bought is above the board as far as I’m concerned. Can let the lawyers fight out the minutia and inevitable licensing specifics after the fact (book publishers are hawks).
Fun fact, did you know that every library in the world has an independent contract with every major book publisher?
In cases I am familiar with, they added a condition that a physical book can only be lent X times. After that, the library must purchase a new copy (even if the original copy is in pristine condition). Yeah, hawks.
This is what I've heard from my friends both there and at Meta. It definitely doesn't carry the prestige it once did. It's more like, "willing to get yelled at, be afraid of being put on a PIP every day, and trying to ensure output outpaces your peers". That's sad, but it's where the industry is at so many places right now.
Amazon offers good signing bonuses that pay out over two years, so it's very common to peace out right at the 2-year mark when your take-home pay abruptly goes way down and the grind is no longer worth it. That's what I did, and I noticed it almost everywhere: there's a constant revolving door of inexperienced people. I don't understand how they keep it going with so much turnover, but somehow they've built a system that kinda withstands it, except in frontier AI apparently.
I think it's coasting on that prestige of being FAANG. People still want it on their resume. I share this from time to time but I interviewed there at the same time I interviewed at Facebook (right before the name change). And the difference was night and day. Amazon truly treated me like cattle. Get in, do the automated Leetcode/HackerRank thing. Canned conversations. Facebook at least _seemed_ like they were rooting for my success the entire time.
If you chart money in your pocket per unit time, it takes a dip around 18 months where your average pay is less than your first month’s pay. (When I was there, using RSU numbers for that time.) Guess when average quitting time was?
HR swore it wasn’t on purpose and I was somehow measuring pay “wrong” by looking at money in my pocket over time; but knowing their HR, I’m sure the valleys in transition from signing bonus to vesting are intentional.
Was s3 the last time Amazon showed lab grade innovation? Lambda?
I could be wrong because I haven't paid much attention but Amazon has just fast followed everyone else innovation for a awhile so it's in like one ecosystem yeah?
I'm not trying to be snarky, I just haven't thought about aws as having any innovation for a while and I always figured it was because ruthless companies that churn through people as disposable commodities generally don't do tech innovation.
I'm talking on the AWS side, on the logistics side they clearly are doing insane things on supply chain perf optimization.
> I could be wrong because I haven't paid much attention but Amazon has just fast followed everyone else innovation for a awhile so it's in like one ecosystem yeah?
A lot of innovation at AWS is invisible on the outside. They pioneered hyperscale datacenters with publicly accessible capacity, software-defined networks, secure VMs, and so on.
> I'm not trying to be snarky, I just haven't thought about aws as having any innovation for a while and I always figured it was because ruthless companies that churn through people as disposable commodities generally don't do tech innovation.
I worked at AWS before COVID. It was really a varied experience, but it was not _bad_ overall. We prided ourselves on making sure our APIs are solid, stable, and backwards compatible. When we had to make a backwards-incompatible change, we actually contacted every affected customer and ensured that their workflows wouldn't be broken.
Amazon Nova is their model? I worked for a company that was being pushed into trying to use AWS's "Nova Act" [0], which I guess was their python-based wrapper to do things in Playwright. I didn't think it used Nova the model under the hood though, or maybe it did. Either way, Nova Act was horrible in terms of performance - it was so...damn...slooooow. Much easier to just use Playwright.
> Amazon’s standout AI model — organized under the name “Nova” — is about the farthest thing from a household name.
I have tried asking people if they've ever used an AI product from certain companies, and you only seem to get "no", or surprise that they have any AI products, for some.
I just played with Nova after seeing this submission. I gave it some real problems for which I used Gemini. It markedly "dumb" in comparison, losing sight of facts that I presented in the first prompt of the chat, and other subsequently introduced, and its responses contain repetitions of the same point-form advice. It's like GPT-3 level or something.
It would seem that they can experience most of the benefit of AI without most of the cost; anthropic is operating at the frontier and shows that even while supplying the best models and token sales to enterprise, they lose massive amounts of money.
Amazon makes 60B+ in profit per year, they don't need to tank that by losing it on training AI / selling tokens.
There are plenty of open weight models out there for it to use with most of the benefit and very little of the downside.
It's possible for both a new technology to be hugely beneficial in the long run & for early investors to lose a lot of money funding it (if they over-invested / over-paid).
Values drive behavior. Who owns / runs futurism and what are their values?
Journalism / media as activity needs to be sustainable and unfortunately in our current world it's seems very difficult to sustainably remain high integrity. Sometimes it may be greed, but most of the time I think it's survival.
In this case AI is part of what is threatening journalist survivability, so it kind of makes sense.
The frontier of AI has gotten so spicy that the delivery risk of pursuing this rabbit is astronomical. Knowing when to quit and use someone else's solution is critical at this scale.
If someone started from zero, how long do we think it would take for them to reach the cost/capability front currently provided by gpt-6.1-terra? How long until OAI figures out a way to distill that down again for pennies on the dollar?
Apple seems to have this sorted. You won't find them chasing OAI, Google and Anthropic around the playground.
I'm not at all close to knowing their internals with books in particular but for most products Amazon has made a significant effort to remove themselves from direct product stocking wherever possible (instead preferring to warehouse other people's stock for efficient shipping). I would guess that they aren't particularly well positioned with publishers at this point... Also, most publishers probably loathe Amazon at this point for all the times Amazon has tried to fleece them w.r.t. Kindle.
Well except for the regular HN anti-AI crowd. Usually the same people that have wished for communism and never ever looked in detail into the 20+ states that failed that way.
their innovation seems to be limited to renaming the forced sidebar on amazon.com every few months and not allowing me to dismiss their useless features.
The chatbot sidebar seems to also be the only way of accessing certain Amazon features, like the price history. And it seems to be implemented in a particularly silly way - clicking the "price history" button prompts the chatbot to show you the price history, rather than just showing it.
Ublock hides the sidebar from me, but it does still take up the whitespace on the side of the screen. Now it won't remember that I dismissed it and it pops back in on every new screen. I am just used to the screen being narrower now. But it is still annoying.
I wonder if the best play now is not to play and wait until the landscape is clear. They are making partnerships now (e.g OpenAI), and investments (e.g. Anthropic).
Wait so Microsoft gutted their AI Division and Microsoft looks like it did as well from the list of "departments" that are in the approved buyout list. Does this mean they are just going to be resellers of the big models companies going forward?
They could revert to the pre-LLM craze where Alexa was actually able to answer prompts in a reasonable amount of time. Alexa is a glorified egg timer for nearly all users - it's super convenient to use a voice prompt to start/stop timers while cooking and being able to play music on voice demand is kinda alright. It genuinely doesn't need to answer hard questions.
The new AI powered Alexa beta basically can't do egg timer, music, or light switch duties as reliably as the old Alexa, which basically makes it useless.
You'd think with all the data collected by these tech companies, they'd understand the common usage scenarios of their products. But instead we have AI Alexa that can't egg timer, or Gemini Assistant that can't navigate or make phone calls.
It doesn't make too much sense for Amazon to invest too much of their own money into AI.
They already sell a lot of the shovels for training and inference and make ample money from that, and there are enough open weight models on the market to make it infeasible to build a large enough moat.
Either you are getting the smartest engineers, or offer the most freedom to pursue interesting goals that aren't on the frontier. Amazon has neither so they naturally aren't going anywhere in that domain.
Anyone that's been in the Amazon offices in the last few years is not likely to have witnessed a culture that fosters lab-grade innovation.
Your comment was likely focused on dysfunctional parts of the culture there (and that seems to be how most replies to you interpreted it as well). There's truth to that, sure. But I think respect for data sensitivity and security is also a big part of what makes the culture ill-suited for frontier AI lab work.
When I was at AWS, we had data access locked down very tightly. I was trying to train a model to predict how long various dynamic workloads running on behalf of customers would take. Just getting access to anonymized production data from a DB that my team owned took well over a month and had me compromise heavily on what attributes I could access. I also spent a decent amount of time in meetings with lawyers and compliance folks to explain and justify all our data classifications for PII, retention, access controls, etc. We would review our data policies quite frequently. We needed break-glass procedures to access prod data in our own systems, and it was uncommon to need to resort to that. Even when you broke glass, certain classes of sensitive data would still not be visible to you. On the plus side, We did get quite good at operating and maintaining systems without needing to see sensitive info.
If you contrast that with Meta's disregard for privacy or the way frontier labs disregard the law, it's easy to see why Amazon would struggle in this space.
I read your comment as “amazon acts too responsibly to be a frontier lab,” and that worries me. That they even bothered to do all that stuff is good. That others don’t is bad.
I did indeed mean it that way, but I agree with you. It sucks, but it's just the unfortunate reality of the world. Many of the most disruptive and successful startups made it there by ignoring legal or moral limitations.
If the people that do stuff well fail, what does that leave us with?
With the need to enact political change so incentives align for the benefit of society at large.
This indeed. Economic democracy is as important as political democracy.
That explains a lot. They are anti “move fast and break things” which is great news for enterprises or anyone seeking stability but terrible for innovation.
I don’t condone the use of pirated content for training. But anything that was bought is above the board as far as I’m concerned. Can let the lawyers fight out the minutia and inevitable licensing specifics after the fact (book publishers are hawks).
Fun fact, did you know that every library in the world has an independent contract with every major book publisher?
In cases I am familiar with, they added a condition that a physical book can only be lent X times. After that, the library must purchase a new copy (even if the original copy is in pristine condition). Yeah, hawks.
There's a reason companies tend to prefer to acquire over in-house. This is part of the calculus.
Amazon chose for itself a reputation as a place that nobody with a choice will work. I'm pleased to see that pay off.
This is a fair take. However, when it comes to warehouse automation/logistics, I constantly see what they're adopting in their hardware stack.
They're a good data point on where the robotics labor frontier is.
So it's a good place to work if you're a robot?
00000000: 6e6f 7420 6576 656e 2061 7320 6120 726f not .even as a ro
00000010: 626f 74
This is what my roomba said when it took me 3 days to find it and cut the hair rolled onto it's wheel.
This is what I've heard from my friends both there and at Meta. It definitely doesn't carry the prestige it once did. It's more like, "willing to get yelled at, be afraid of being put on a PIP every day, and trying to ensure output outpaces your peers". That's sad, but it's where the industry is at so many places right now.
Amazon offers good signing bonuses that pay out over two years, so it's very common to peace out right at the 2-year mark when your take-home pay abruptly goes way down and the grind is no longer worth it. That's what I did, and I noticed it almost everywhere: there's a constant revolving door of inexperienced people. I don't understand how they keep it going with so much turnover, but somehow they've built a system that kinda withstands it, except in frontier AI apparently.
I think it's coasting on that prestige of being FAANG. People still want it on their resume. I share this from time to time but I interviewed there at the same time I interviewed at Facebook (right before the name change). And the difference was night and day. Amazon truly treated me like cattle. Get in, do the automated Leetcode/HackerRank thing. Canned conversations. Facebook at least _seemed_ like they were rooting for my success the entire time.
They still pay a lot. The comment you replied to is mostly wrong about the 2 year cliff. Year 3 and 4 should be higher comp if you have good ratings.
Exact same experience.
Amazons interviews were so formulaic and it’s interviewers so robotic it was almost sickening.
Works great for the business too. I recently worked in a business unit with a 2 year vesting model. I loved the work and challenges.
.. and then got let go at 22 months in favour of the AI budget.
Gotta respect the hustle.
If you chart money in your pocket per unit time, it takes a dip around 18 months where your average pay is less than your first month’s pay. (When I was there, using RSU numbers for that time.) Guess when average quitting time was?
HR swore it wasn’t on purpose and I was somehow measuring pay “wrong” by looking at money in my pocket over time; but knowing their HR, I’m sure the valleys in transition from signing bonus to vesting are intentional.
Is this weeding out long termers (willing to wait years to vest) vs the impatient?
Was s3 the last time Amazon showed lab grade innovation? Lambda?
I could be wrong because I haven't paid much attention but Amazon has just fast followed everyone else innovation for a awhile so it's in like one ecosystem yeah?
I'm not trying to be snarky, I just haven't thought about aws as having any innovation for a while and I always figured it was because ruthless companies that churn through people as disposable commodities generally don't do tech innovation.
I'm talking on the AWS side, on the logistics side they clearly are doing insane things on supply chain perf optimization.
> I could be wrong because I haven't paid much attention but Amazon has just fast followed everyone else innovation for a awhile so it's in like one ecosystem yeah?
A lot of innovation at AWS is invisible on the outside. They pioneered hyperscale datacenters with publicly accessible capacity, software-defined networks, secure VMs, and so on.
> I'm not trying to be snarky, I just haven't thought about aws as having any innovation for a while and I always figured it was because ruthless companies that churn through people as disposable commodities generally don't do tech innovation.
I worked at AWS before COVID. It was really a varied experience, but it was not _bad_ overall. We prided ourselves on making sure our APIs are solid, stable, and backwards compatible. When we had to make a backwards-incompatible change, we actually contacted every affected customer and ensured that their workflows wouldn't be broken.
Nitro?
This article was published on July 29th. I’m not saying it may not still be interesting or whatever but I thought that was worth pointing out.
Anything AI related is going to start needing [month] tags.
> Amazon Is Gutting Its AI Division [July]
Indeed. I read this news around that time. I thought just now they did second round of AI purge.
Amazon Nova is their model? I worked for a company that was being pushed into trying to use AWS's "Nova Act" [0], which I guess was their python-based wrapper to do things in Playwright. I didn't think it used Nova the model under the hood though, or maybe it did. Either way, Nova Act was horrible in terms of performance - it was so...damn...slooooow. Much easier to just use Playwright.
[0] https://nova.amazon.com/act
> Amazon’s standout AI model — organized under the name “Nova” — is about the farthest thing from a household name.
I have tried asking people if they've ever used an AI product from certain companies, and you only seem to get "no", or surprise that they have any AI products, for some.
I just played with Nova after seeing this submission. I gave it some real problems for which I used Gemini. It markedly "dumb" in comparison, losing sight of facts that I presented in the first prompt of the chat, and other subsequently introduced, and its responses contain repetitions of the same point-form advice. It's like GPT-3 level or something.
It would seem that they can experience most of the benefit of AI without most of the cost; anthropic is operating at the frontier and shows that even while supplying the best models and token sales to enterprise, they lose massive amounts of money.
Amazon makes 60B+ in profit per year, they don't need to tank that by losing it on training AI / selling tokens.
There are plenty of open weight models out there for it to use with most of the benefit and very little of the downside.
"With urgent questions swirling over whether LLMs can ever usher in a return on investment — let alone AGI"
It will always remain weird to me that a publication called Futurism is so outright negative towards our newest technologies.
It's possible for both a new technology to be hugely beneficial in the long run & for early investors to lose a lot of money funding it (if they over-invested / over-paid).
Because anyone can apply any label to anything.
Values drive behavior. Who owns / runs futurism and what are their values?
Journalism / media as activity needs to be sustainable and unfortunately in our current world it's seems very difficult to sustainably remain high integrity. Sometimes it may be greed, but most of the time I think it's survival.
In this case AI is part of what is threatening journalist survivability, so it kind of makes sense.
Anyone that was any good in the AI space has long since fled Amazon/AWS. It’s just a sea of mediocrity on AI. Thus nobody is surprised by this.
The frontier of AI has gotten so spicy that the delivery risk of pursuing this rabbit is astronomical. Knowing when to quit and use someone else's solution is critical at this scale.
If someone started from zero, how long do we think it would take for them to reach the cost/capability front currently provided by gpt-6.1-terra? How long until OAI figures out a way to distill that down again for pennies on the dollar?
Apple seems to have this sorted. You won't find them chasing OAI, Google and Anthropic around the playground.
https://blog.google/company-news/inside-google/company-annou...
I mean, you don't start from zero, you distill everyone else's models....
Just occurred to me that Amazon seems interestingly positioned relative to the book sourcing thing. I guess that's still not enough.
I'm not at all close to knowing their internals with books in particular but for most products Amazon has made a significant effort to remove themselves from direct product stocking wherever possible (instead preferring to warehouse other people's stock for efficient shipping). I would guess that they aren't particularly well positioned with publishers at this point... Also, most publishers probably loathe Amazon at this point for all the times Amazon has tried to fleece them w.r.t. Kindle.
Original Business Insider article was submitted several months ago: 6 upvotes, 2 comments:
https://news.ycombinator.com/item?id=49082344
This isn't a blip on anyone's radar.
Well except for the regular HN anti-AI crowd. Usually the same people that have wished for communism and never ever looked in detail into the 20+ states that failed that way.
In Soviet Capitalism, model employs YOU.
Note that to someone who's been unemployed for uncomfortably long under Regular Capitalism might be interested.
That oughta fix it.
“So… what happened to the previous team?”
"Instead, labor and computing power are being diverted toward a singular “frontier-model effort”".
If true, Amazon is not really gutting its AI division.
Despite it being an old article things for amazon haven't changed:
you want edge inference, from decision to small models.
That's it. It will be 2c, please.
You want to be edging.
Amazon operates by capturing others margin, they’re just waiting for more to develop
Well lately they are capturing their customers' margin for sure.
any to develop?
Story from July OP;
Source: https://www.businessinsider.com/amazon-overhauls-ai-strategy...
Couple comments then:
https://news.ycombinator.com/item?id=49082344
3 cheers for bezos!
their innovation seems to be limited to renaming the forced sidebar on amazon.com every few months and not allowing me to dismiss their useless features.
The chatbot sidebar seems to also be the only way of accessing certain Amazon features, like the price history. And it seems to be implemented in a particularly silly way - clicking the "price history" button prompts the chatbot to show you the price history, rather than just showing it.
Ublock hides the sidebar from me, but it does still take up the whitespace on the side of the screen. Now it won't remember that I dismissed it and it pops back in on every new screen. I am just used to the screen being narrower now. But it is still annoying.
oof the sidebar on mobile is killing me
AI labs are first research stuff. We see the things that work, but we all know that a lot of stuff in research fails. Nobody publishes their failures.
This is something that requires an ethos completely different from how amazon works and the way jeff bezos sees the world.
I started seeing so many ads for their SDK strands or something on reddit, so badly wanting tbe community to pick it up
I wonder if the best play now is not to play and wait until the landscape is clear. They are making partnerships now (e.g OpenAI), and investments (e.g. Anthropic).
Wait so Microsoft gutted their AI Division and Microsoft looks like it did as well from the list of "departments" that are in the approved buyout list. Does this mean they are just going to be resellers of the big models companies going forward?
And yet Amazon has Alexa. They have a user base for a smart chatbot. What's Alexa going to run on for hard questions?
Alexa+ was their LLM based release and to my knowledge it was an utter disaster and failure of product development.
Latency is the #1 UX killer on voice apps, and the latency was terrible compared to Alexa. I used it for like 15 minutes and reverted.
They could revert to the pre-LLM craze where Alexa was actually able to answer prompts in a reasonable amount of time. Alexa is a glorified egg timer for nearly all users - it's super convenient to use a voice prompt to start/stop timers while cooking and being able to play music on voice demand is kinda alright. It genuinely doesn't need to answer hard questions.
The new AI powered Alexa beta basically can't do egg timer, music, or light switch duties as reliably as the old Alexa, which basically makes it useless.
You'd think with all the data collected by these tech companies, they'd understand the common usage scenarios of their products. But instead we have AI Alexa that can't egg timer, or Gemini Assistant that can't navigate or make phone calls.
Here's how to fix it: "Alexa, exit Alexa plus".
Alexa had already been using other models like Claude depending on the question, and the French version for example uses Mistral.
Basic pre-LLM speech-to-text and a passthrough to duckduckgo would beat their current product, so...
It doesn't make too much sense for Amazon to invest too much of their own money into AI.
They already sell a lot of the shovels for training and inference and make ample money from that, and there are enough open weight models on the market to make it infeasible to build a large enough moat.
Amazon doesn’t seem to agree:
> Instead, labor and computing power are being diverted toward a singular “frontier-model effort”
It’s a consolidation, not a withdrawal.
[dead]