zlacker

>>tablet+(OP)
One thing that I find truly amazing is just the simple fact that you can now be fuzzy with the input you give a computer, and get something meaningful in return. Like, as someone who grew up learning to code in the 90s it always seemed like science fiction that we'd get to a point where you could give a computer some vague human level instructions and get it more or less do what you want.

>>gdubs+Z
It's mind blowing. At least 1-2x/week I find myself shocked that this is the reality we live in

>>csalle+z1
It’s surreal to me been using ChatGPT everyday for 2 years, makes me question reality sometimes like ‘howtf did I live to see this in my lifetime’

I’m only 39, really thought this was something reserved for the news on my hospital tv deathbed.

>>mentos+W4
Ok, but do you not remember IBM Watson beating the human players on Jeopardy in 2011? The current NLP based neural networks termed AI isn't so incredibly new. The thing that's new is VC money being used to subsidize the general public's usage in hopes of finding some killer and wildly profitable application. Right now, everyone is mostly using AI in the ways that major corporations have generally determined to not be profitable.

>>hattma+CS
That 'Watson' was fully purpose built though and ran on '2,880 POWER7 processor threads and 16 terabytes of RAM'.

'Watson' was amazing branding that they managed to push with this publicity stunt, but nothing generally useful came out of it as far as I know.

(I've worked with 'Watson' products in the past and any implementation took a lot of manual effort.)

>>wicked+Ug1
Watson is more generally the computer system that was running the LLM. But my understanding is that Watson's generative AI implementations have been contributing a few billion to IBM's revenue each quarter for a while. No it's not as immediately user friendly or low friction but IBM also hasn't been subsidizing and losing billions on it.

>>hattma+SQ1
What they had in the Jeopardy era was far from an LLM or GenAI. From what I've been able to deduce, they had a massive Lucene index of data that they expected to be relevant for Jeopary. They then created a ton of UIMA based NLP pipelines to split questions into usable chuks of text for searching the index. Then they had a bunch of Jeopardy specific logic to rank the possible answers that the index provided. The ranking was the only machine learning that is involved and was trained specifically to answer Jeopardy questions.

The Watson that ended up being sold is a brand, nothing more, nothing less. It's the tools they used to build the thing that won Jeopardy, but not that thing. And yes, you're right that they managed to sell Watson branded products, I worked on implementing them in some places. Some were useless, some were pretty useful and cool. All of them were completely different products sold under the Watson brand and often had nothing in common with the thing that won Jeopardy, except for the name.