121–130 of 264 posts
Undoubtedly IBM has done amazing work popularizing AI with Jeopardy and the debate bot. However, I think that halo extended to its competitors that, frankly, offer more things developers really need.
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That's surely part of the problem, but the catalyst is the marketing strategy that is used to brainwash the employees. In essence; sell the experience, not the product. This works well for IBM generally (the products are shit) but especially well for Watson because it's extremely easy to sell AI without getting bogged down in details. You want to identify brain tumors? We'll just teach Watson to do it. Whilst IBM res…
> This works well for IBM generally (the products are shit) but especially well for Watson because it's extremely easy to sell AI without getting bogged down in details. The cynic in me says that every use of the term AI in any capacity is to sell experience and not functionality. When was the last time you used a product billed as 'AI' and thought 'wow, this is a huge game changer'? Siri is cool, but it's ultimately…
You severely underestimate the bandwidth of your eyes and ears and other senses, and the volume of your brain's memory (despite it's uber-loosy compression). That's terabytes a day probably, if not big data than I dunno what is. Yeah, 99% of it is thrown away at passing through the first few hundreds of layers of your neural networks, but they still know what to throw away...
To get a digital computer on "equal" terms with the zillions of hacky optimizations your semi-analog brain uses you need a shitton of raw power and data volume ("if you don't know what to throw away of the input data, you need to just sift through all/more of it") to compensate for the fact that you don't have N million years of evolution to devise similar hacky optimizations.
Also, humans work as a "network of agents", that's also recurrent (aka "culture"). Current sub-human-level AI agents are far from any sort of reliable interop.
My guess is that we'll get human level performance levels at AGI tasks when we learn to build swarms of AI-agents that cooperate well and "model each other", and few people are working on this... Heck, when it happens it will probably be an "accident" of some IoT optimizations thing, like, "oops, the worldwide network of XYZ industrial monitoring agents just reached sentience and human level intelligence bc it was the only way it could solve the energy-efficiency requirement goals it was tasked to optimize for" :)
I've never interacted directly with IBM, but I remember about 2 years ago, they had a talk at the Akamai Edge conference about how they dealt with bloated cookies. The company I work for has the same problem so I sat in to see what their solution was. The problem they were having is that all the various IBM lines of business added so much garbage onto the client's cookie, that eventually their pages would stop loadin…
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> This works well for IBM generally (the products are shit) but especially well for Watson because it's extremely easy to sell AI without getting bogged down in details. The cynic in me says that every use of the term AI in any capacity is to sell experience and not functionality. When was the last time you used a product billed as 'AI' and thought 'wow, this is a huge game changer'? Siri is cool, but it's ultimately…
> humans can extrapolate and make reliable predictions about the future based on really small sample sizes You severely underestimate the bandwidth of your eyes and ears and other senses, and the volume of your brain's memory (despite it's uber-loosy compression). That's terabytes a day probably, if not big data than I dunno what is. Yeah, 99% of it is thrown away at passing through the first few hundreds of layers o…
Sample size and record size are two different things.
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> IBM is just too big to get out of its own way Brilliantly put Funny thing is, when it did get out of its own way, what did we get? The IBM PC
...A very successful platform. Just not for IBM.
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It was totally rule-based. More complex systems had a little more probabilistic stuff via Bayes and "certainty factors", but not this one. I worked on another one for this company called Vibration Advisor which diagnosed odd noises in GM cars.
Being rules based isn't necessarily a bad thing or disingenuous. I develop healthcare AI products (ML/DL researcher) and we actually aim to be able to translate our models into a rules based engine (find a strong signal, interpret/understand model well enough to translate/embed into a rules engine, look for a new signal in our models, rinse + repeat). We end up deploying a mix of rules based and true ML based models…
Are we close to it being technically feasible , leaving aside regulation and interpersonal qualities doctors bring to the table ?
Isn't this just the same problem IBM has had for...well...most of my adult life? I had a contract gig at IBM Advanced Technology in Boca for about 18 months in early 2001-2002. Talk about missing the boat... I was brought in to prop up a soon-to-be-failed project for the Japanese government...basically a "Napster for Tokyo" that would allow paid-for-play C2C song sharing for customers of "the Big 5" record companies.…
Getting a nice check while doing nothing actually productive is soul crushing. Good for the short term but it's a Chinese water torture in the long run. Two years ago at their vegas conference they had a coffee shop that used AI to recommend coffee types. I thought "boy, they don't understand this technology".
Earlier quoted context omitted.
That's surely part of the problem, but the catalyst is the marketing strategy that is used to brainwash the employees. In essence; sell the experience, not the product. This works well for IBM generally (the products are shit) but especially well for Watson because it's extremely easy to sell AI without getting bogged down in details. You want to identify brain tumors? We'll just teach Watson to do it. Whilst IBM res…
> Whilst IBM research might be able to pull it off, it'll never get to market because there is nobody capable of making good products at IBM anymore. As an ex-IBMer this is so true and so frustrating at the same time. Engineers are thrashed about on a nearly sprintly basis by PM's with short attention spans and no understanding of how disruptive their continuously changing requirements are. It doesn't help that IBM c…
This stuff is the friggen worst if you ask me. i'm so done with the AI hype train and IBM is the worst. Linked article mentions a 'watsons law' (similar to moore's law etc). If you ask me, it is more likely for watsons law to be that all commercial BigCo 'AI' offerings will burn thru hundreds of millions and ultimately fail rather then the intended meaning. "Phytel’s contribution was analytics paired with an automate…
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> IBM is just too big to get out of its own way Brilliantly put Funny thing is, when it did get out of its own way, what did we get? The IBM PC
...A very successful platform. Just not for IBM.