mobrec

So
So much unnecessary anthropomorphizing happening in the Machine Learning (aka Artificial Intelligence) space. From calling outright fabrications of 'data' 'Hallucinations' to claiming human emotions (“I'm sorry I couldn't help with that....”) and giving human names to interfaces, the discussions in these areas continue to be muddied more than clarified.

When Taylor Webb played around with GPT-3 in early 2022, he was blown away by what OpenAI’s large language model appeared to be able to do. Here was a neural network trained only to predict the next word in a block of text—a jumped-up autocomplete. And yet it gave correct answers to many of the abstract problems that Webb set for it—the kind of thing you’d find in an IQ test. “I was really shocked by its ability to solve these problems,” he says. “It completely upended everything I would have predicted.”

Webb is a psychologist at the University of California, Los Angeles, who studies the different ways people and computers solve abstract problems. He was used to building neural networks that had specific reasoning capabilities bolted on. But GPT-3 seemed to have learned them for free.

Last month Webb and his colleagues published an article in Nature, in which they describe GPT-3’s ability to pass a variety of tests devised to assess the use of analogy to solve problems (known as analogical reasoning). On some of those tests GPT-3 scored better than a group of undergrads. “Analogy is central to human reasoning,” says Webb. “We think of it as being one of the major things that any kind of machine intelligence would need to demonstrate.”

What Webb’s research highlights is only the latest in a long string of remarkable tricks pulled off by large language models. For example, when OpenAI unveiled GPT-3’s successor, GPT-4, in March, the company published an eye-popping list of professional and academic assessments that it claimed its new large language model had aced, including a couple of dozen high school tests and the bar exam. OpenAI later worked with Microsoft to show that GPT-4 could pass parts of the United States Medical Licensing Examination.

And multiple researchers claim to have shown that large language models can pass tests designed to identify certain cognitive abilities in humans, from chain-of-thought reasoning (working through a problem step by step) to theory of mind (guessing what other people are thinking). 

Such results are feeding a hype machine that predicts computers will soon come for white-collar jobs, replacing teachers, journalists, lawyers and more. Geoffrey Hinton has called out GPT-4’s apparent ability to string together thoughts as one reason he is now scared of the technology he helped create. 

But there’s a problem: there is little agreement on what those results really mean. Some people are dazzled by what they see as glimmers of human-like intelligence; others aren’t convinced one bit.

“There are several critical issues with current evaluation techniques for large language models,” says Natalie Shapira, a computer scientist at Bar-Ilan University in Ramat Gan, Israel. “It creates the illusion that they have greater capabilities than what truly exists.”

https://www.technologyreview.com/2023/08/30/1078670/large-language-models-arent-people-lets-stop-testing-them-like-they-were

So
Why is the media so focused on the most despicable, vile, self-serving garbage in society (rhymes with Melon Husk) when humble, dedicated people like Jose Andres actually works to help people in need?

Before chef José Andrés became famous for World Central Kitchen, he had already scaled the heights of his profession. His new cookbook celebrates the group's humanitarian impact.

“I remember this Spanish guy screaming,” said chef-volunteer Karla Hoyos, describing the first time she met chef José Andrés. “He had just come from a meeting with FEMA [the US emergency management agency], and he was furious. And I thought, 'Oh, no, no, nooo…'.” She shakes her head emphatically. “I am not going to deal with this person. I don't care who he is.”

It was September 2017, shortly after Hoyos had arrived in Puerto Rico following Hurricane Maria, the deadly storm that devastated the island, killing nearly 3,000 people, making most roads impassable and knocking out 80% of the power grid. Several days earlier, Andrés had touched down with a team from his non-profit, World Central Kitchen (WCK), which he founded in 2010 after returning from Haiti where he fed survivors of a catastrophic earthquake. The organisation originally emphasised longer-term programmes – such as supporting nutritional training for young mothers – but after Maria, its efforts now focus on deploying an army of culinary first responders to feed people during and after the world's worst disasters, natural or otherwise.

https://www.bbc.com/travel/article/20230911-jos-andrs-the-man-who-created-an-army-of-culinary-first-responders

So
Lots to chew on in this article.

I think the real challenge is in letting corporations set their own 'standards' you end up with a bunch of standards that only suit that particular corporation.

So
I had to laugh out loud at the sheer intellectual dis-ingenuousness of these write ups, featured most frequently and prominently in right wing leaning outlets.

Basically, the story is a Florida-guy buys a discontinued electric vehicle then looks into having the battery replaced only to find that it would cost more than the car. But wait, the battery is not available to purchase in the first place (then, how, you might ask, were they given a price for replacing it?) So the clear take away from that isn't 'know what you are buying' it is 'ALL Electric Cars Are Bad'. Morons

So by extension, I buy a used, discontinued iPhone for $50 and drop it. The shop says that it will cost me $250 to have the screen replaced. And I can't replace the battery, because, you know, that 'discontinued' part. Therefore, iPhones in particular and mobile phones in general are bad, evil and we should have never gotten rid of phone booths. Because some people have the logic and reasoning capabilities of dryer lint.

So
BMW recently made the misguided decision to charge a subscription for heated seats in some markets. Aside from the fact that the average BMW is a maintenance disaster and is nearly undriveable by its 3rd year, what is the point of charging a subscription for a fairly standard car feature? Simple greed.

Consider also that every one of those vehicles has the added expense of being fitted with the heating elements and controls that may not be enabled. That seems like wasted money unless the consumer is actually paying for the feature twice: once when it is priced into the cost of manufacturing the car and *again* when the consumer actually tries to use it.

The other problem with these feature flags hidden in your car is that not only BMW can have access to them. It is not a great leap to imagine a new form of ransomware where you have to pay BMW and then some hacker to re-re-re-enable a feature on your vehicle.

So
> “I use multi-factor authentication on every web site that I can – that way no one can track me.” > > Yeah, I am pretty sure that isn't how that works, self-proclaimed cyber security 'expert' on a podcast

So
This is a bit of a departure from the tech-oriented articles that I usually post but I thought I would just “put this out there” because I couldn't find any relevant info when I had this issue with this product.

Basically, the Jotul GV 370 DV is a gas stove (the kind you use to heat a room, not to cook on). It was installed and minimally tested for gas flow. The problem was, it wouldn't stay lit when we tried to use it for the first time. The pattern was, the pilot would light, 30-90 seconds would go by, the stove would flash combust (the gas in the chamber would ignite) rather forcefully but not stay on. This cycle would continue until a red LED on the front of the control unit started flashing. At this point, I turned off the stove and turned of the gas and started looking for answers.

I read and re-read the installation docs that came with the Jotul GV 370 DV. One thing I noticed is that the damper setting on it was not correct for the amount of vent pipe that was installed. That was an easy fix. Unfortunately, it didn't solve the problem (or change it at all). Internet searches didn't reveal any additional useful information, just a couple of edge cases and people arguing philosophy rather than practice solutions.

I even tried the justAnswers web site. Paid $5 for a 'trial membership' and was connected to an absolutely useless 'expert' who just tried to read me the online posts I had found via google. His final bit of 'expert advice' was to get a voltage meter, disassemble the stove and tell him what all the voltage readings were on all the stove components. Absolutely pointless exercise. I thanked him for wasting my time and requested a refund from justAnswers.

At this point, I elected to take the glass off the front of the unit and inspect the burning media bed to make sure the gas jets weren't blocked or obstructed. This is when I noticed that the gas bed was out of alignment with the pilot starter. I removed the gas bed tray, re-seated it so that the notch for the pilot was centered on the pilot (instead of all the way to the right like it was when i originally opened it up). After this adjustment, I carefully placed the gas bed media back on the pan, reassembled the glass and turned the gas back on.

When I turned on the stove, the pilot came on, 30 seconds later the perimeter of the bed lit, went out, re-lit, then stayed on. Success! All that because of a one centimeter misalignment of the gas bed with the pilot.

So there you have it. Hopefully this will help someone else who has this issue quickly solve the problem without delay or 'expert' help.

So
This article reinforces what I have been saying for years: microservices are a big mistake, especially for developers who don't understand distributed systems, high availability and observability. To be successful, they must be properly designed and implemented, unlike most of the copy-and-paste, we-don't-need-no-stinkin-design development that is seen today.

From the article:

We engineers have an affliction. It’s called “wanting to use the latest tech because it sounds cool, even though it’s technically more difficult.” Got that from the doctor’s office, it’s 100% legit. The diagnosis was written on my prescription for an over-the-counter monolith handbook. From 2004. Seriously though, we do this all the time. Every time something cool happens, we flock to it like moths to a campfire. And more often than not, we get burned.

So
This feels like an extension of ethics, in general, not being part of the curriculum in education.

Anaconda’s survey of data scientists from more than 100 countries found the ethics gap extends from academia to industry. While organizations can mitigate the problem through fairness tools and explainability solutions, neither appears to be gaining mass adoption.

Only 15% of respondents said their organization has implemented a fairness system, and just 19% reported they have an explainability tool in place.

The study authors warned that this could have far-reaching consequences:

Above and beyond the ethical concerns at play, a failure to proactively address these areas poses strategic risk to enterprises and institutions across competitive, financial, and even legal dimensions.

The survey also revealed concerns around the security of open-source tools and business training, and data drudgery. But it’s the disregard of ethics that most troubled the study authors:

Of all the trends identified in our study, we find the slow progress to address bias and fairness, and to make machine learning explainable the most concerning. While these two issues are distinct, they are interrelated, and both pose important questions for society, industry, and academia.

While businesses and academics are increasingly talking about AI ethics, their words mean little if they don’t turn into actions.

So

I think these lessons have application beyond the Cloud and AWS