7 ms·

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

by krona 8y ago

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 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.

appstateguy 8y ago
> 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 consistently puts the cart before the horse is even born and pivots multiple teams all at the same time such that nothing you build upon is stable or consistent. Working there was maddening.
- haskellandchill 8y ago
  I think this is just what large multinationals do these days.
- workinthehead 8y ago
  Sounds like the way non-tech companies operate. Pretty damning that IBM can't understand why leadership of a tech company should have a tech background.
cirgue 8y ago
> 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 not super useful. Google translate is incredible, but it can only do what it can do because of the absolutely mind-boggling amount of training data that google can access. Most disciplines have the problem of not enough data, despite what 'big-data' folks say. In contrast, humans can extrapolate and make reliable predictions about the future based on really small sample sizes. We can pick up a new skill or recognize a new pattern with a high degree of accuracy really effing fast compared to a computer. This gives humans an enormous advantage. If IBM and anyone else in this space were really focused on delivering excellent real-world results, step 0 is building out world-class data integration and search tools (which we still actually suck at, weirdly.)
- NicoJuicy 8y ago
  Many people mention even a worser search experience with Google and AI
  - davidf18 8y ago
    Could you please elaborate? Does that include DeepMind?
- mlthoughts2018 8y ago
  In fact, I would say apart from maybe self-driving cars, almost all of the biggest gains from machine learning are in unsexy, hidden backend problems, like automatically rectifying disparate data, optimizing resource utilization, flagging difficult-to-articulate events or triggers in a stream of data too large for human evaluation, machine translation, and other “unsexy” things. Product interfaces usually offer simple features to users and the value proposition is easy to see. Effective use of machine learning is well hidden upstream in a bunch of unsexy preprocessing or heavy lifting to get to the interface. Not something you’d ever need to emphasize in marketing, except maybe at tech meetups or in recruiting materials, but not to the end consumer. It just makes pop references to AI-powered products more egregious.
- nostrademons 8y ago
  I use & depend upon plenty of products that are built upon AI - GMail spam filtering & categorized inbox, Google image search, YouTube & Netflix recommendations, cheque OCR at my ATM, predictive keyboards on my phone, Amazon's "people also buy with this product" feature, Google translate, computer opponents in games that I play, and all of the signals that feed into Google Search. The irony is that not one of these bills itself as AI. It's just "a product that works", and the company that produces it is happy to keep the details secret and let users enjoy the product. So you may be right that the term "AI" itself is pure salesmanship. When it starts to work it ceases to be AI. https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect Also - humans only look like we're fast at picking up new domains because we apply a helluva lot of transfer learning, and most "new" domains aren't actually that different from our previous experiences. Drop a human in an environment where their sensory input is truly novel - say, a sensory deprivation tank where all visual & auditory stimulation is random noise - and they will literally go insane. I've got a 5-month-old and a project where I'm attempting to use AI to parse webpages, and I will bet you that I can teach my computer to read the web before I can teach my kid to do so.
ThomPete 8y ago
Agree. Consultancies rarely sell products or solutions. Instead they sell project management by making it sound like you are a more safe bet than a smaller product studio who actually do make products work. Its a real shame but i mostly blame the zero mistake KPI culture primarily fueled by how managers on the client side are promoted.
mathattack 8y ago
Over the past 10 years I’ve been surprised when anyone smart would join IBM. I understand why people hung on, but why join that dying ship? Now I can’t think of any still there.
- occamrazor 8y ago
  Who says IBM is dying? They aren’t anymore (since a long time) at the bleeding edge of research, but they still have a solid consulting and integration business. They also offer decent salaries and good opportunities for sales-oriented technical people. It wouldn’t be my first choice of employer, however I can see how some people would enjoy working there.
  - mathattack 8y ago
    Dying may be extreme. Perhaps it’s safer to say that they are in the mode of returning capital to investors rather than growing. I’m at a large customer of theirs and they are bleeding the customer for every dollar as they get phased out. Very low caliber of services professionals too.

by krona 8y ago

appstateguy 8y ago

> 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 consistently puts the cart before the horse is even born and pivots multiple teams all at the same time such that nothing you build upon is stable or consistent. Working there was maddening.

haskellandchill 8y ago
I think this is just what large multinationals do these days.
workinthehead 8y ago
Sounds like the way non-tech companies operate. Pretty damning that IBM can't understand why leadership of a tech company should have a tech background.

cirgue 8y ago

> 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 not super useful. Google translate is incredible, but it can only do what it can do because of the absolutely mind-boggling amount of training data that google can access. Most disciplines have the problem of not enough data, despite what 'big-data' folks say. In contrast, humans can extrapolate and make reliable predictions about the future based on really small sample sizes. We can pick up a new skill or recognize a new pattern with a high degree of accuracy really effing fast compared to a computer. This gives humans an enormous advantage. If IBM and anyone else in this space were really focused on delivering excellent real-world results, step 0 is building out world-class data integration and search tools (which we still actually suck at, weirdly.)

NicoJuicy 8y ago
Many people mention even a worser search experience with Google and AI
- davidf18 8y ago
  Could you please elaborate? Does that include DeepMind?
mlthoughts2018 8y ago
In fact, I would say apart from maybe self-driving cars, almost all of the biggest gains from machine learning are in unsexy, hidden backend problems, like automatically rectifying disparate data, optimizing resource utilization, flagging difficult-to-articulate events or triggers in a stream of data too large for human evaluation, machine translation, and other “unsexy” things. Product interfaces usually offer simple features to users and the value proposition is easy to see. Effective use of machine learning is well hidden upstream in a bunch of unsexy preprocessing or heavy lifting to get to the interface. Not something you’d ever need to emphasize in marketing, except maybe at tech meetups or in recruiting materials, but not to the end consumer. It just makes pop references to AI-powered products more egregious.
nostrademons 8y ago
I use & depend upon plenty of products that are built upon AI - GMail spam filtering & categorized inbox, Google image search, YouTube & Netflix recommendations, cheque OCR at my ATM, predictive keyboards on my phone, Amazon's "people also buy with this product" feature, Google translate, computer opponents in games that I play, and all of the signals that feed into Google Search. The irony is that not one of these bills itself as AI. It's just "a product that works", and the company that produces it is happy to keep the details secret and let users enjoy the product. So you may be right that the term "AI" itself is pure salesmanship. When it starts to work it ceases to be AI. https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect Also - humans only look like we're fast at picking up new domains because we apply a helluva lot of transfer learning, and most "new" domains aren't actually that different from our previous experiences. Drop a human in an environment where their sensory input is truly novel - say, a sensory deprivation tank where all visual & auditory stimulation is random noise - and they will literally go insane. I've got a 5-month-old and a project where I'm attempting to use AI to parse webpages, and I will bet you that I can teach my computer to read the web before I can teach my kid to do so.

ThomPete 8y ago

Agree. Consultancies rarely sell products or solutions. Instead they sell project management by making it sound like you are a more safe bet than a smaller product studio who actually do make products work. Its a real shame but i mostly blame the zero mistake KPI culture primarily fueled by how managers on the client side are promoted.

mathattack 8y ago

Over the past 10 years I’ve been surprised when anyone smart would join IBM. I understand why people hung on, but why join that dying ship? Now I can’t think of any still there.

occamrazor 8y ago
Who says IBM is dying? They aren’t anymore (since a long time) at the bleeding edge of research, but they still have a solid consulting and integration business. They also offer decent salaries and good opportunities for sales-oriented technical people. It wouldn’t be my first choice of employer, however I can see how some people would enjoy working there.
- mathattack 8y ago
  Dying may be extreme. Perhaps it’s safer to say that they are in the mode of returning capital to investors rather than growing. I’m at a large customer of theirs and they are bleeding the customer for every dollar as they get phased out. Very low caliber of services professionals too.