Look I think everybody needs to cut IBM some slack here. Integrating technology with customer needs is hard, and it takes a while to get good at it, to get a process for reconciling with product managers want with what developers can actually make. Once IBM has been in this technology game for a little while, I'm sure they'll get the hang of it.
Layoffs at Watson Health Reveal IBM’s Problem with AI
91–100 of 264 posts
Re: Layoffs at Watson Health Reveal IBM’s Problem with AI
#92"Offering managers didn’t have technical backgrounds and sometimes came up with ideas for new products that were simply impossible." Sounds like they drank their own kool-aid, e.g., "Products That Enhance and Amplify Human Expertise," rather than understand the actual limitations and possibilities of ML. And it seems to me that they're still doing it with this nonsense about a human-level "AI" debating stack. The ove…
There's a pretty good podcast interview with Eugene Dubossarsky that has relevant discussion about issues with management and data science in general. https://www.datafuturology.com/podcast/1 Here are a few of my notes (my words not the interviewee's): - in order to use data science, you have to have creative people thinking about data on the front end - they don't have to be data scientists, but they need to be crea…
This is a great summary. I think his guideposts are helpful for most decision support initiatives, whether you're using data to try and support decisions, or reaching out to humans.
We run prediction markets inside companies and find that if we don't establish a good lifecycle of asking forecasting questions, having people respond with probabilities, then decision makers REACTING to those probabilities in some way (whether they agree with them or not, just acknowledge their existence) the likelihood of the project failing is far higher.
Re: Layoffs at Watson Health Reveal IBM’s Problem with AI
#93"Offering managers didn’t have technical backgrounds and sometimes came up with ideas for new products that were simply impossible." Sounds like they drank their own kool-aid, e.g., "Products That Enhance and Amplify Human Expertise," rather than understand the actual limitations and possibilities of ML. And it seems to me that they're still doing it with this nonsense about a human-level "AI" debating stack. The ove…
IMO, this is a bigger issue in the industry. People are hyping up ML/AI to the point where the actual application is either impossible or extremely difficult. Just look at how many people are so fearful of AI/ML taking away jobs and replacing humans. Anyone in the field knows that AI/ML can take away jobs but it is more of the low-end jobs and everything happens gradually rather than immediately. AI/ML is being more as a tool to enhance human productivity rather than as a direct replacement for entire occupations unless the job is very basic to begin with.
Re: Layoffs at Watson Health Reveal IBM’s Problem with AI
#94I'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 loading because they wouldn't be able to parse the cookie.
The 'solution' is to detect when that's about to happen, and redirect the client to a page that warns them that their cookie is too big (because IBM made it too big) and give them a button to delete their cookie. They then continue to start over and stuff more garbage into the fresh cookie.
That kind of problem solving pretty much made me lose faith in them successfully doing much of anything anymore.
Re: Layoffs at Watson Health Reveal IBM’s Problem with AI
#95Earlier quoted context omitted.
> amazing information retrieval system Which I imagine still has lots of value on it's own for large, complicated data sets.
Yep. But if your marketing and product management are all focused on selling AI instead of IR, then they're not really working toward finding a way to deliver the IR value they have to the people who need it. I'd actually like to give Watson a spin for an IR problem I'm looking at, but, thanks to their hype machine being set to overdrive, they've got the thing priced in the "The Bold Leaders of the Future Creating a…
What is your use case and what are the alternatives you're considering? I'm trying to understand what to imagine here.
Re: Layoffs at Watson Health Reveal IBM’s Problem with AI
#96"Offering managers didn’t have technical backgrounds and sometimes came up with ideas for new products that were simply impossible." Sounds like they drank their own kool-aid, e.g., "Products That Enhance and Amplify Human Expertise," rather than understand the actual limitations and possibilities of ML. And it seems to me that they're still doing it with this nonsense about a human-level "AI" debating stack. The ove…
The article only mentions the engineers being laid off, not the managers who botched it, nor the executives who hired with incompetence. The reward structure of such a corporate environment would seem counter-intuitive to success.
Re: Layoffs at Watson Health Reveal IBM’s Problem with AI
#97Earlier quoted context omitted.
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 b…
None of the things you mentioned are even close to AI. They’re applied statistics, and they mostly use techniques we’ve known about for decades but have only now found a use case because computing and storage is cheap enough to make them viable.
The recommendation, translation, & image classification algorithms are all done with deep-learning; that's considered AI now.
There was a time, not all that long ago, when SVMs, Bayesian networks, and perceptrons were considered AI. That's behind the spam filters, predictive keyboards, and most of the search signals.
There was a time, a bit longer ago, when beam search and A* were considered AI. That's behind the game opponents.
As the linked Wikipedia article says, "AI is whatever we don't know how to do yet." There will be a time (rapidly approaching) where deep learning and robotics are common knowledge among skilled software engineers, and we won't consider them AI either. We'll find something else to call AI then, maybe consciousness or creativity or something.
Re: Layoffs at Watson Health Reveal IBM’s Problem with AI
#98Every Watson ad I see on TV freaks me the hell out. Seeing primetime television commercials for business AIs feels too uncomfortably cyberpunk for me
Re: Layoffs at Watson Health Reveal IBM’s Problem with AI
#99I'm in my final week at a large company and so much of this article rings true for me as well. I feel like the structure required to coordinate really big companies has some really negative emergent properties that make it very difficult for such a company to be efficient and innovative.
Look at a company like Google, which, without a doubt, has some of the best engineers in the world. How many false starts and just flat out poorly executed projects/products have they had in the last 10 years? Way more than you would expect from a company that puts such a premium on hiring the best.
Re: Layoffs at Watson Health Reveal IBM’s Problem with AI
#100The problem at IBM is not technological; it's managerial . For a long while now, IBM has been treating "AI" as a product that can be managed, packaged, and sold by "general" business managers -- think MBA-types with only a superficial, qualitative grasp of deep learning and AI. Doing that with rapidly evolving technology is a sure-fire recipe for failure . Most such MBA-types today are ill-equipped to manage, package…
MBAs vs. undergrads with liberal arts degrees is a whole other discussion. An argument can definitely be made for a liberal arts skill-set in terms of adaptability and capacity to quickly learn other skills/subjects. Not sure if that encompasses something as complicated or esoteric as the technicalities of AI/ML, though.
To be honest, I would rather work for someone who just got an undergrad liberal arts degree, who is aware they don't know technology. They can learn, and there's plenty of stuff about communicating with (and for) customers that I don't know or don't do well, so it can work well. Which is all theoretically true of an MBA too, but...