251–260 of 348 posts
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If they resurected Clippy and made it the face of their Ai I would switch in a heartbeat.
https://felixrieseberg.github.io/clippy/
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>I've interviewed several people who were affected by these layoffs, and honestly, many of them were mediocre engineers by most measures. But that still doesn't make this a path to success. How mediocre are we talking about here? (I’m curious)
Very poor & mediocre. You can find secret little pockets within Microsoft where individuals & small teams do nothing at all, day in and day out. I mean literally nothing. The game is to maximize life and minimize work at the expense of the company. The managers are in on the game and help with the cover-up. I find it hilariously awesome and kind of sad at the same time. Anyway, one round of layoffs this year was spec…
I'm sure it's difficult enough for people to find work right now without you putting a knife in their back on the way out.
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Why is this, I wonder? Aren't the models trained on about the same blob of huggingface web scrapes anyway? Does one tool do a better job of pre-parsing the web data, or pre-parsing the prompts, or enhancing the prompts? Or a better sequence of self-repair in an agent-like conversation? Or maybe more precision in the weights and a more expensive model?
> Why is this, I wonder? because that's Microsoft's business model their products are just just good enough to allow them to put a checkbox in a feature table to allow it to be sold to someone who will then never have to use it but not even a penny more will be spent than the absolute bare minimum to allow that this explains Teams, Azure, and everything else they make you can think of
I hear tales of the before-times, when they had a QA department and took quality seriously.
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Agreed! I recently listened to a podcast (video) from the "How Money Works" channel on this topic: "How Short Term Thinking Won" - https://youtu.be/qGwU2dOoHiY The author argues that this con has been caused by three relatively simple levers: Low dividend yields, legalization of stock buybacks, and executive compensation packages that generate lots of wealth under short pump-and-dump timelines. If those are the cause…
What is wrong with stock buybacks? Genuine question, I don't understand the economics of the stock market and as such I participate very little (probably to my detriment) I sort of figure the original theory went like this. "We have an idea to run a for profit endeavor but do not have money to set it up. If you buy from us a portion of our future profit we will have the immediate funds to set up the business and you…
The short answer is that the trend of frequent stock buybacks as discussed here is not being used to "eliminate debt" (restore private ownership), it's being used to puff up the stock price as a non-taxable alternative to dividend payouts (simply increasing the stock price by reducing supply does not realize any gains, while paying stockholders "interest" directly is subject to income tax). This games the metric of "stock price", which is used as a proxy for all sorts of things including executive performance and compensation.
As someone who appreciates machine learning, the main dissonance I have with interacting with Microsoft's implementation of AI feels like "don't worry, we will do the thinking for you". This appears everywhere, with every tool trying to autocomplete every sentence and action, creating a very clunky ecosystem where I am constantly pressing 'escape' and 'backspace' to undo some action that is trying to rewrite what I a…
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Don’t attribute to malice that which can equally be contributed to incompetence. I think you’re over-estimating the capabilities of these tech leaders, especially when the whole industry is repeating the same thing. At that point, it takes a lot of guts to say “No, we’re not going to buy into the hype, we’re going to wait and see” because it’s simply a matter of corporate politics: if AI fails to deliver, it fails to…
> Don’t attribute to malice that which can equally be contributed to incompetence. This discourse needs to die. Incompetence + lack of empathy is malice. Even competence in the scenario they want to create is malice. It's time to stop sugar-coating it.
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> Why is this, I wonder? because that's Microsoft's business model their products are just just good enough to allow them to put a checkbox in a feature table to allow it to be sold to someone who will then never have to use it but not even a penny more will be spent than the absolute bare minimum to allow that this explains Teams, Azure, and everything else they make you can think of
* That's modern Microsoft's desktop product business model I hear tales of the before-times, when they had a QA department and took quality seriously.
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>I've interviewed several people who were affected by these layoffs, and honestly, many of them were mediocre engineers by most measures. But that still doesn't make this a path to success. How mediocre are we talking about here? (I’m curious)
Aren't most of us mediocre?
Is this “they’re not Carmack”? “They messed up their explanation or the CAP theorem”? “They can’t write a for loop”?
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Very poor & mediocre. You can find secret little pockets within Microsoft where individuals & small teams do nothing at all, day in and day out. I mean literally nothing. The game is to maximize life and minimize work at the expense of the company. The managers are in on the game and help with the cover-up. I find it hilariously awesome and kind of sad at the same time. Anyway, one round of layoffs this year was spec…
Damn that is crazy, how do you measure it? , AI use? , i hope you saying this doesn't affect the employment prospects of the ones that aren't "mediocre" but happened to be on those teams. I'm sure it's difficult enough for people to find work right now without you putting a knife in their back on the way out.
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Is she going to pay enough to fund the multitrillion dollars it costs to run the current AI landscape?
Yeah, she is, because when reality sets in, these models will probably have monthly cellphone/internet level costs. And training is the main money sink, whereas inference is cheap. 500,000,000 people paying $80/mo is roughly a 5-yr ROI on a $2T investment. I cannot believe on a tech forum I need to explain the "Get them hooked on the product, then jack up the price" business model that probably 40% of people here are…
False. Training happens once for a time period, but inference happens again and again every time users use the product. Inference is the main money sink.
"according to a report from Google, inference now accounts for nearly 60% of total energy use in their AI workloads. Meta revealed something even more striking: within their AI infrastructure, power is distributed in a 10:20:70 ratio among experimentation, training, and inference respectively, with inference taking the lion’s share."
https://blogs.dal.ca/openthink/the-hidden-cost-of-ai-convers...