Man, I know people love to throw the word “dystopian” around, but holy shit is that description dystopian as fuck.

Amazon Mechanical Turk (MTurk) is a crowdsourcing marketplace that makes it easier for individuals and businesses to outsource their processes and jobs to a distributed workforce who can perform these tasks virtually. This could include anything from conducting simple data validation and research to more subjective tasks like survey participation, content moderation, and more. MTurk enables companies to harness the collective intelligence, skills, and insights from a global workforce to streamline business processes, augment data collection and analysis, and accelerate machine learning development.

I thought that was a fake joke website but it’s real???

Welcome to the world of venture capitalism. It’s all “come on, guy! This is the next thing! Trust me bro!”

What’s surprising is more and more people keep falling for it.

Like 20-30 years ago it made sense. But we have “kids” all the way up to their 20s who literally grew up in this over hyped environment that still believe all this bullshit is days away from changing the world.

It’s like a cult insisting the Messiah is coming back tomorrow, and every night the day “to morrow for sure”

seems like chip designers are being a lot more conservative from a design perspective. NPUs are generally a shitton of 8 bit registers with optimized matrix multiplication. the “AI” that’s important isn’t the stuff in the news or the startups; it’s the things that we’re already taking for granted. speech to text, text to speech, semantic analysis, image processing, semantic search, etc, etc. sure there’s a drive to put larger language models or image generation models on embedded devices, but a lot of these applications are battle tested and would be missed or hampered if that hardware wasn’t there. “AI” is a buzz word and a goalpost that moves at 90 mph. machine learning and the hardware and software ecosystem that’s developed over the past 15 or so years more or less quietly in the background (at least compared to ChatGPT) are revolutionary tech that will be with us for a while.

blockchain currency never made sense to me from a UX or ROI perspective. they were designed to be more power hungry as adoption took off, and power and compute optimizations were always conjecture. the way wallets are handled and how privacy was barely a concern was never going to fly with the masses. pile on that finance is just a trash profession that requires goggles that turn every person and thing into an evaluated commodity, and you have a recipe for a grift economy.

a lot of startups will fail, but “AI” isn’t going anywhere. it’s been around as long as computers have. i think we’re going to see a similarly (to chip designers) cautious approach from companies like Google and Apple, as more semantic search, image editing, and conversation bot advancements start to make their way to the edge.

I would prefer builtin not very powerful FPGA’s getting into consumer hardware.

I never quite got that. Apple boys and commercials alsways treated siri like that smart, super useful thing that can answer questions and is basically a thinking being. In reality it’s some speech to text google machine that can do a few things sometimes. Same with the android equivalent, i use it to set a timer while cooking, for the life of me i can’t imagine using it for anything else.

Were all iOS 5 Siri requests manually answered by Susan Bennett, the original voice actor?

You’re completely missing the point.

It’s portrayed as all AI to get investors, but in reality most of the “human help” end up having to do like 90% of the work.

But the company runs around telling potential investors lies to get money

I worked in the object recognition and computer vision industry for almost a decade. That stuff works. Really well, actually.

But this checkout thing from Amazon always struck me as odd. It’s the same issue as these “take a photo of your fridge and the system will tell you what you can cook”. It doesn’t work well because items can be hidden in the back.

The biggest challenge in computer vision is occlusion, followed by resolution (in the context of surveillance cameras, you’re lucky to get 200x200 for smaller objects). They would have had a really hard, if not impossible, time getting clear shots of everything.

My gut instinct tells me that they had intended to build a huge training set over time using this real-world setup and hope that the sheer amount of training data could help overcome at least some of the issues with occlusion.

That’s not AI tho. Like on any level.

Calling that AI is marketing or a lie.