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.
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.
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.
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.
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.
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.
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.
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.
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 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.
Exact same experience.
Amazons interviews were so formulaic and it’s interviewers so robotic it was almost sickening.
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.
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.
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.
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.
"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.
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.
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...
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.
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.
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.
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.
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
And yet Amazon has Alexa. They have a user base for a smart chatbot. What's Alexa going to run on for hard questions?
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.
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.
I started seeing so many ads for their SDK strands or something on reddit, so badly wanting tbe community to pick it up