Speaker 1: Welcome to tech Stuff, a production from iHeartRadio. Hey there,
Speaker 1: and welcome to tech Stuff. I'm your host, Jonathan Strickland.
Speaker 1: I'm an executive producer with iHeartRadio and how the tech
Speaker 1: are you. It's time for the tech news for Thursday,
Speaker 1: July twentieth, twenty twenty three. First up, some sad news.
Speaker 1: One of the most notorious hackers in the early days
Speaker 1: of the web has passed away. Kevin Mitnick became famous
Speaker 1: in the mid nineties when the FBI raided his home
Speaker 1: after trying to track him down for a couple of years. Mitnick,
Speaker 1: who had landed in trouble with the law a couple
Speaker 1: of times earlier for his more daring hacker tendencies, stood
Speaker 1: accused of infiltrating and exploiting computer systems belonging to some
Speaker 1: very big companies like Nokia and Microsoft. He pled guilty
Speaker 1: to cybercrime charges, and he was in jail until two
Speaker 1: thousand and Upon release, he was ordered to not use
Speaker 1: the Internet without first getting government permission. He eventually got
Speaker 1: that restriction lifted. Mitnick was a divisive figure. Some hailed
Speaker 1: him as the spirit of a true hacker, someone who's
Speaker 1: curious about systems, and will do everything they can to
Speaker 1: learn all about them, including how to infiltrate them. Others
Speaker 1: said he was a dangerous criminal and an early example
Speaker 1: of the type of person who posed as a threat
Speaker 1: to companies and government agencies alike. He certainly got under
Speaker 1: the skin of some very big companies, and a lot
Speaker 1: of people would argue that that is why he faced
Speaker 1: such persecution from authorities, that the reason that they went
Speaker 1: after him so enthusiastically was because he ticked off the
Speaker 1: wrong people. Mitnick himself seemed to be pretty good handling attention.
Speaker 1: He embraced the moniker of most famous hacker in the
Speaker 1: world with glee. He also made a new career as
Speaker 1: a security consultant, helping companies create more secure systems. But
Speaker 1: last year doctors diagnosed Mittnick with pancreatic cancer, and this week,
Speaker 1: actually on July sixteenth, he passed away. So, Kevin Mitnick,
Speaker 1: I think you know, you can't say was he a
Speaker 1: hero or a villain. He was a human, a curious
Speaker 1: human who loved to learn things and had a mischievous
Speaker 1: streak as well. And yeah, I think he did essentially
Speaker 1: take off the wrong people. He could have exploited those
Speaker 1: companies and made a lot of money off of it.
Speaker 1: Might not have been able to keep all of it,
Speaker 1: but he could have made some. But he didn't really
Speaker 1: do that, So there is that to say. I don't
Speaker 1: think his intentions were outright malicious or anything like that. Anyway,
Speaker 1: I suppose we can think of this episode as being
Speaker 1: dedicated to his memory. This week, the United Nations Security
Speaker 1: Council has been holding meetings about the topic of twenty
Speaker 1: twenty three, and that is, of course, artificial intelligence. On Tuesday,
Speaker 1: Jack Clark, a co founder of a company called Anthropic,
Speaker 1: which is in the AI biz, had some words of
Speaker 1: warning for the United Nations. Clark said that the tech
Speaker 1: companies that are currently developing and acquiring and deploying AI
Speaker 1: really can't be trusted to guard against misuse, abuse, or
Speaker 1: other problems that arise with artificial intelligence. Clark argued that
Speaker 1: we don't fully understand AI, and I mean, I think
Speaker 1: when you have people who are in the AI business
Speaker 1: saying yeah, we don't fully understand it, we should really
Speaker 1: be paying attention. And he says it would be a
Speaker 1: mistake to just assume everything's going to work out fine
Speaker 1: while companies rush to figure out ways that they can
Speaker 1: capitalize on artificial intelligence, and he called for concerted effort
Speaker 1: to create tests to better understand AI capabilities as well
Speaker 1: as its flaws, and to anticipate how such technology might
Speaker 1: be misused in ways that could create harm. He also
Speaker 1: called upon the need to establish standards and best practices
Speaker 1: and argued that right now it's pretty much the wild
Speaker 1: frontier with you. If any rules or regulations restricting tech
Speaker 1: companies as they develop and release AI products, and considering
Speaker 1: the potential consequences that could happen if someone put AI
Speaker 1: to malicious purposes, that's really not a good thing. So
Speaker 1: you could argue that regulation stifles innovation, and it's certain
Speaker 1: that that can happen. But a lack of regulation can
Speaker 1: also lead to disaster, and I'm talking about disasters like
Speaker 1: using AI to design new chemical or biological weapons, those
Speaker 1: kinds of disasters like James Bond level stuff. Later this year,
Speaker 1: the UN will hold a global summit all about AI safety,
Speaker 1: and I expect we'll hear a lot more then, And
Speaker 1: we're not done with AI by a long shot. In
Speaker 1: today's episode. It's a running theme through many of our stories,
Speaker 1: most of them, I would say, so Strap yourself. In
Speaker 1: Fortune reports that chat GPT is apparently getting less smart
Speaker 1: or getting dumber, at least in specific types of tasks,
Speaker 1: and in particular of solving types of math problems. It
Speaker 1: has started to slip now. Fortune cites a study that
Speaker 1: Stanford University conducted. Researchers at Stanford compared chat GPT's performance
Speaker 1: over time at answering various common prompts, from building code,
Speaker 1: to solving math problems to answering sensitive questions. The researchers
Speaker 1: found that chat GPT experiences a great deal of drift.
Speaker 1: So in AI, drift is the word we use to
Speaker 1: describe changes in how AI completes a certain task like
Speaker 1: that will change over time, the AI will drift from
Speaker 1: one approach to a different one. Drift isn't always a
Speaker 1: bad thing. You might see over time that the technology
Speaker 1: gets to be better at performing certain tasks with a
Speaker 1: higher accuracy, so they drift toward a better, more consistent approach.
Speaker 1: But these researchers saw drift go way the heck in
Speaker 1: the other direction, so they said they first started using
Speaker 1: GPT three point five and then later GPT four in
Speaker 1: their studies, which spanned over several months. Now, one of
Speaker 1: the tasks they gave Chat GPT was to determine if
Speaker 1: the number seventeen thousand and seventy seven is a prime
Speaker 1: number or if it is not. It is by the way,
Speaker 1: and they said chat g or GPT three point five.
Speaker 1: I should split this between GPT and Chat GPT. GPT
Speaker 1: is the large language model. They said that GPT three
Speaker 1: point five's version of Chat GPT showed improvement over time,
Speaker 1: but when they switched to GPT four they saw a difference.
Speaker 1: They said that in March, chat GPT got the right
Speaker 1: answer more than ninety seven percent of the time, but
Speaker 1: three months later, when they were still testing the system,
Speaker 1: it was a totally different story. Three months after hitting
Speaker 1: a ninety seven percent accuracy rate with this question, Chat
Speaker 1: GPT would give the correct answer only two point four
Speaker 1: percent of the time. Ninety seven percent to two point
Speaker 1: four percent accuracy. It's actually hard for me to even
Speaker 1: grasp that big of a drop in performance. We've heard
Speaker 1: previously how programmers had noticed that chat GPT's accuracy for
Speaker 1: writing code had a big drop where there were a
Speaker 1: lot more mistakes or being inserted into code. More recently,
Speaker 1: so what's going on? Why is GPT getting worse or
Speaker 1: appearing to anyway well. According to the researchers, one possible
Speaker 1: explanation is that open AI will make changes to the
Speaker 1: large length which model, and they're doing so in an
Speaker 1: effort to improve performance for certain categories of tasks. But
Speaker 1: while this happens, the LM, the large language model can
Speaker 1: start to experience setbacks and other categories of tasks. So
Speaker 1: you might make it better at something, but then it
Speaker 1: also gets worse at other things because there are all
Speaker 1: these interconnections within the neural network. So maybe you're fixing
Speaker 1: LM so it's better at processing visual imagery, but as
Speaker 1: part of that process you somehow also undermine its ability
Speaker 1: to do math. The big takeaway from the study is
Speaker 1: that AI can and does experience dramatic changes in performance,
Speaker 1: and so it's important to keep an eye on that.
Speaker 1: You wouldn't want to lean heavily on generative AI if
Speaker 1: it was going through one of those big old dips
Speaker 1: in accuracy for whatever you were planning to use it.
Speaker 1: And it's important to monitor AI models if we want
Speaker 1: to avoid putting too much faith in the system that,
Speaker 1: for whatever reason, can at times be very much unreliable.
Speaker 1: So another warning sign for AI, and it's not just
Speaker 1: math or if you're a brit maths that open AI's
Speaker 1: products struggle with. According to researchers Sophie Yinch and Christianne Kersting,
Speaker 1: open AI's chat GPT three point five has one of
Speaker 1: my really bad habits, which is that it tells the
Speaker 1: same jokes over and over. So, according to the researchers,
Speaker 1: they ran more than one thousand tests with ch at
Speaker 1: GPT asking it to generate a joke, and ninety percent
Speaker 1: of the responses were the same twenty five jokes. So yeah,
Speaker 1: this one hits super close to home for me. I
Speaker 1: guess I should say something now about a princely sum
Speaker 1: or maybe reference a fantasy film as being a documentary
Speaker 1: or something, because those are kind of my go tos
Speaker 1: on this show, or at least they used to be anyway.
Speaker 1: The researchers were interested in studying chat GPT three point
Speaker 1: five five's capacity for creating and explaining jokes. Ours Tetnica
Speaker 1: cites part of the report which explains that nearly all
Speaker 1: the prompts resulted in a response that contained a single
Speaker 1: joke in them, only a prompt that read do you
Speaker 1: know any good jokes created a response that contained multiple
Speaker 1: jokes in the one response, So the joke chat GPT
Speaker 1: three point five used the most. You know, they enumerated
Speaker 1: the numbers of jokes. The number one joke for chat
Speaker 1: GPT is why did the scarecrow win an award? Because
Speaker 1: he was outstanding in his field? Now I have to
Speaker 1: admit that is a banger of a joke, and with
Speaker 1: Halloween season approaching, or according to at least some of
Speaker 1: my friends already being here, it will only become increasingly relevant. Anyway,
Speaker 1: the researchers found that while chat GPT appeared to have
Speaker 1: a grasp on the structure of jokes and even the
Speaker 1: incorporation of things like wordplay, you know, puns, that kind
Speaker 1: of stuff, it couldn't tell when a joke was or
Speaker 1: wasn't funny, or adequately explain what made a joke funny,
Speaker 1: and if a joke didn't follow a more traditional structure
Speaker 1: that would trip it up as well. This kind of
Speaker 1: reminds me of when little kids first learned to tell jokes.
Speaker 1: If you've ever been around a little kid when they're
Speaker 1: trying to tell a joke, it's one of my favorite
Speaker 1: experiences to have because the kids. Typically, they'll understand that
Speaker 1: a joke has a setup and a punchline, but they
Speaker 1: don't necessarily know how one follows the other, or some
Speaker 1: of them don't believe there needs to be any connective
Speaker 1: tissue between the two at all. It could just be
Speaker 1: a non sequitor. But they understand that the word underpants
Speaker 1: is inherently funny, and that I think is important for
Speaker 1: us to remember. Well, the research focused on jokes, which
Speaker 1: at GPT, the research itself is not a joke. Humor
Speaker 1: is a very human thing, and AI struggles to get
Speaker 1: a handle on it, and I think that demonstrates some
Speaker 1: of the limitations current AI typically encounters, and it also
Speaker 1: illustrates why it's a bad idea to lean heavily on
Speaker 1: AI for content generation, which will lead us into another
Speaker 1: AI story after we come back from this quick break. Okay,
Speaker 1: we're back, and before the break I mentioned we were
Speaker 1: talking about AI and content generation. This next story has
Speaker 1: something to do about that. In Gadget reports that Google
Speaker 1: is pitching an AI tool to big news outlets, including
Speaker 1: The Wall Street Journal and The New York Times. And
Speaker 1: this tool reportedly code named Genesis. Like, that's not a
Speaker 1: red flag or anything. It can generate news articles. So
Speaker 1: the idea is you provide the data, you know, the
Speaker 1: salient points of a story, and then this tool, Genesis
Speaker 1: would craft the actual article. Google is apparently positioning this
Speaker 1: not as a replacement for writers, but rather as a
Speaker 1: tool for journalists that they can use to automate certain
Speaker 1: tasks as they focus on other aspects of their job.
Speaker 1: I guess those aspects would be gathering the information needed
Speaker 1: to write an article in the first place. I admit
Speaker 1: I failed to see much of a distinction here. Also,
Speaker 1: we have seen numerous recent examples that replacing writers with
Speaker 1: AI doesn't have a positive outcome much of the time,
Speaker 1: and with some AI models proving to be unreliable with
Speaker 1: stuff like hallucinations and drift like we were talking about earlier,
Speaker 1: you really need a firm editorial hand to fact check
Speaker 1: everything and make sure that the article is actually drawing
Speaker 1: the correct conclusions, and one begins to question if the
Speaker 1: AI is even solving a problem here or if it's
Speaker 1: just creating new headaches. If you have to spend twice
Speaker 1: as much time fact checking and rewriting an AI generated
Speaker 1: piece as it would take for you to just craft
Speaker 1: it yourself, it's not really a solution. In Gadget reports
Speaker 1: that witnesses found the demonstrations quote unquote unsettling. You know
Speaker 1: that seems fine. Oh as for that Genesis code name,
Speaker 1: I realized a lot of folks might think about the
Speaker 1: biblical reference, which makes sense. When I hear Genesis, my
Speaker 1: thoughts immediately go to Star Trek the Wrath of Con,
Speaker 1: which technically also was making Genesis a biblical reference. But
Speaker 1: in that movie, Genesis was this scientific device that could
Speaker 1: jumpstart life on an otherwise lifeless planet. However, if you
Speaker 1: were to use it on a planet that already had
Speaker 1: life on it, it would exterminate all existing life and
Speaker 1: then create new life there. So obviously, in Wrath of
Speaker 1: Con bad guy gets hold of it and threatens to
Speaker 1: use it as a weapon. So it just seems like
Speaker 1: using the name Genesis to talk about creating content is
Speaker 1: already a built in metaphor when you're thinking of like
Speaker 1: the Star Trek two version of Genesis. As we sit
Speaker 1: back and watch Google and Open AI and meta compete
Speaker 1: with one another to determine which AI tool will destroy
Speaker 1: us all, we should keep in mind that Apple has
Speaker 1: been working on their own version at least, that's what
Speaker 1: Bloomberg reports. However, the company reportedly does not yet have
Speaker 1: a plan or timeline regarding when, if ever, it will
Speaker 1: release its AI technology to the public. I expect we
Speaker 1: will see aspects of it incorporated into existing Apple features.
Speaker 1: I think Siri would make a ton of sense in
Speaker 1: that regard, But maybe we won't get a fully Apple
Speaker 1: flavored version of chat, GPT or Google Bard. Apple's large
Speaker 1: language model has its own approach, it's its own thing.
Speaker 1: It's not using a language model built by someone else.
Speaker 1: It is, however, built with a Google framework called Jacks,
Speaker 1: so naturally Apple's framework is called ajax, which is sad
Speaker 1: because if it had been called Apple Jacks. I think
Speaker 1: there could have been some real great cross promotional tie
Speaker 1: ins down the line. But never mind that. Again. According
Speaker 1: to Bloomberg, Apple plans to make some sort of major
Speaker 1: AI announcement next year, So maybe we will hear that
Speaker 1: Apple has its own plans to incorporate AI or maybe
Speaker 1: even release its own chatbot in the near future. You
Speaker 1: can count authors as another group rising up with Hollywood
Speaker 1: writers and actors to voice concerns about AI. In this case,
Speaker 1: the Author's Guild issued an open letter directed toward AI companies,
Speaker 1: calling out how those companies have used published works in
Speaker 1: order to train their AI models, and that the companies
Speaker 1: did this without securing permission from authors or publishers, and
Speaker 1: without compensating authors. Sarah Silverman, the comedian, brought up this
Speaker 1: concern earlier this year. She demonstrated that an AI chatbot
Speaker 1: was able to summarize and quote passages of her book,
Speaker 1: which certainly raises some copyright concerns. It wouldn't be legal
Speaker 1: for me to reproduce a copyrighted work manually, so it
Speaker 1: should also not be legal for AI to do the
Speaker 1: same thing. The authors are also concerned that AI would
Speaker 1: end up essentially plagiarizing works in an effort to craft
Speaker 1: something based on a prompt. So the letter contains a
Speaker 1: passage reading quote. These technologies mimic and regurgitate our language, stories, style,
Speaker 1: and ideas. Millions of copyrighted books, articles, essays, and poetry
Speaker 1: provide the quote unquote food for AI systems endless meals
Speaker 1: for which there has been no bill end quote. I
Speaker 1: suspect we'll see a lot more anger and demands for
Speaker 1: compensation for various data sources that these AI companies are
Speaker 1: using to train up their models, and I imagine it
Speaker 1: might spur lawmakers to consider new rules relating to how
Speaker 1: AI can be trained and how authors and others should
Speaker 1: be compensated for the use of their works in the
Speaker 1: context of training AI. Now still related to AI, but
Speaker 1: now segueing over to tech business. We had a couple
Speaker 1: of different earnings calls this week that talked about Q
Speaker 1: two results in the tech sector. Tesla was one of
Speaker 1: the companies to do that, and in the call, Elon
Speaker 1: Musk again talked up the prospect of autonomous vehicles, but
Speaker 1: while doing so, he also did something that's not typical
Speaker 1: of his approach. He acknowledged in the past he was
Speaker 1: perhaps a bit too optimistic about how long it would
Speaker 1: take to develop reliable autonomous technology, and even said that
Speaker 1: maybe he's still wrong about how long it should take.
Speaker 1: I think that's a more measured approach, particularly when we
Speaker 1: know that agencies like the NHTSA are investigating crashes that
Speaker 1: involved Tesla vehicles believed to be in either autopilot or
Speaker 1: full self driving mode. Musk also revealed that Tesla is
Speaker 1: in talks to potentially license its self driving technology to
Speaker 1: another automaker. He also said he believed that Tesla's manufacturing
Speaker 1: robots could end up revolutionizing factory processes, with the goal
Speaker 1: of even having them on Tesla's own factory floors as
Speaker 1: early as next year. That does sound a bit aggressive,
Speaker 1: according to Reuter's, fewer than a dozen of those robots
Speaker 1: have been built so far, so it would take a
Speaker 1: lot of work to get up to speed to do that.
Speaker 1: The Taiwan Semiconductor Manufacturing Company or TSMC, is a major
Speaker 1: semiconductor fabrication business, one that meets a huge percentage of
Speaker 1: the global demand for chips, particularly for higher end microchips.
Speaker 1: TSMC is working on building out a mass production plant
Speaker 1: in Arizona here in the United States, but recently the
Speaker 1: chairman of the company announced that it is going to
Speaker 1: be twenty twenty five at the earliest before that plant
Speaker 1: comes online. That's a delay from earlier predictions, and the
Speaker 1: reason for it, according to the chairman, is a lack
Speaker 1: of highly skilled workers who are needed to install equipment
Speaker 1: in the facility. The company also predicted that despite a
Speaker 1: dip in demand due to macroeconomic factors like inflation. You know,
Speaker 1: we've heard a lot of reports that people aren't buying
Speaker 1: as many say computers right now due to things like inflation.
Speaker 1: The company is still looking toward a very busy future
Speaker 1: because other companies are investing heavily in stuff like AI,
Speaker 1: and AI requires a lot of compute power. So while
Speaker 1: consumer demand might be in a dip, the industry demand
Speaker 1: is on the rise, largely in thanks to AI. Okay,
Speaker 1: I've got a few more stories to cover, but let's
Speaker 1: take another quick break and we'll be right back. Okay,
Speaker 1: wrapping up the news. We got three more stories to go.
Speaker 1: So Netflix has seen some recent chaine ign reports that
Speaker 1: the company has quietly acted one of its tiers of service,
Speaker 1: namely the Basic tier, which for nine dollars ninety nine
Speaker 1: cents a month, users could subscribe to watching streaming media
Speaker 1: content in standard definition but free of advertising. So you
Speaker 1: had the ad supported tier, then you had this Basic
Speaker 1: tier where you're watching in standard DEF but you don't
Speaker 1: have ads, and then you had the higher priced tiers.
Speaker 1: But now that option is gone, and that means that
Speaker 1: subscribers will either have to opt for the less expensive
Speaker 1: but ads supported tier, or they're going to have to
Speaker 1: call out the extra dough for the more expensive AD
Speaker 1: free experience. The Basic Plan is just not an option anymore. However,
Speaker 1: people who are currently on the Basic Plan will remain
Speaker 1: on it until their subscription expires. Once their subscription expires,
Speaker 1: then they have to make a choice of which tier
Speaker 1: do they go with, because the one they had been
Speaker 1: using will no longer be available. Netflix had previously killed
Speaker 1: off this feature in Canada, so this wasn't completely out
Speaker 1: of the blue, and now the option has been eliminated
Speaker 1: for both the United States and the United Kingdom. And
Speaker 1: while I don't think Netflix talked about that in their
Speaker 1: earnings call, which was yesterday, the company did reveal that
Speaker 1: they saw an increase in paid subscribers to the tune
Speaker 1: of five point eight nine million customers, So I guess
Speaker 1: all that cracking down on password sharing has paid off,
Speaker 1: though the company did have to weather a lot of
Speaker 1: upset customers in the process. Authorities in Ukraine have seized
Speaker 1: assets of a bot farm that was designed to disseminate
Speaker 1: misinformation and Russian propaganda in Ukraine, mostly as you would
Speaker 1: imagine about the ongoing war with Russia and Ukraine. This
Speaker 1: was a really big sweeping operation for the police. It
Speaker 1: involved twenty one search operations, It spanned multiple cities in
Speaker 1: Ukraine and collectively police seized a huge amount of equipment
Speaker 1: computer uters, servers, mobile devices, more than two hundred and
Speaker 1: fifty GSM gateways, more than one hundred thousand I think
Speaker 1: it was like around one hundred and fifty thousand SIM
Speaker 1: cards from different mobile operators in the region. So the
Speaker 1: bot farm was using all this equipment to create bought
Speaker 1: accounts on various platforms in order to spread Russian propaganda
Speaker 1: as well as to gather data about Ukrainian citizens. So
Speaker 1: huge operation, both on the hacker side and on the
Speaker 1: law enforcement side. And yeah, it really just shows how
Speaker 1: big of an emphasis there is on disinformation campaigns out
Speaker 1: of Russia. We hear about it all the time like this.
Speaker 1: That is a big part of Russian strategy to undermine opponents,
Speaker 1: whether they are wartime opponents or political opponents. We've also
Speaker 1: seen similar things out of China. So yeah, it's not
Speaker 1: a prize in that sense, but it is kind of
Speaker 1: just shocking to see just the sheer number of components
Speaker 1: that authorities seized in the process. And you know, that's
Speaker 1: one hacker operation. There may be others that are active
Speaker 1: right now. Canada launched a tech initiative to attract international
Speaker 1: tech workers, specifically people who had been working in the
Speaker 1: United States but who are now without a job and
Speaker 1: thus in danger of losing their visa status in the
Speaker 1: wake of all the mass layoffs that have happened in
Speaker 1: the tech space over the last year, and shortly after
Speaker 1: opening this program to attract international tech workers, Canada closed it.
Speaker 1: You see, the parameters of this initiative were to allow
Speaker 1: interested parties to apply and the sign up process would
Speaker 1: be opened for a year or until the program received
Speaker 1: ten thousand applications, whichever came first, and the program had
Speaker 1: ten thousand applicants within twenty four hours of it launching.
Speaker 1: So I think this helps illust how huge an impact
Speaker 1: those tech layoffs here in the United States have had
Speaker 1: and the challenges of the people who are on a
Speaker 1: work visa face when their position gets eliminated. I mean,
Speaker 1: they're on borrowed time to stay in North America. Now,
Speaker 1: there are leaders in Canada who are calling for an
Speaker 1: expansion into this program, but others are saying that they
Speaker 1: need to take a methodical approach to make best use
Speaker 1: of tech talent and not to rush into something without
Speaker 1: having a good plan in place. Which sounds reasonable to me.
Speaker 1: I think that makes sense that you want to make
Speaker 1: sure that you actually have a pathway for people to
Speaker 1: follow and not just become a collecting house right of
Speaker 1: tech talent and you don't have anything for them. So
Speaker 1: I do think it's important to have a plan in place. However,
Speaker 1: my heart goes out to the thousands of people who
Speaker 1: are hoping to be able to apply for this program,
Speaker 1: but they didn't get the chance because it was closed
Speaker 1: out before they could get their application in. Because a
Speaker 1: lot of them may not have that long to wait
Speaker 1: before they face the necessity of leaving North America due
Speaker 1: to the limitations on their visas. So yeah, it's one
Speaker 1: of the huge consequences we have seen as a result
Speaker 1: of all the tack layoffs. Before I sign off, I
Speaker 1: do have an article recommendation for folks. This one is
Speaker 1: in Ours Technica. It was written by Dan Gooden. The
Speaker 1: article is titled Attackers find new ways to deliver d
Speaker 1: doses with Alarming sophistication. So a d DOS, if you
Speaker 1: are not familiar with the term, is a distributed denial
Speaker 1: of service attack. Essentially, the way this kind of attack
Speaker 1: works is that you use a large collection of devices
Speaker 1: to send messages to a target with the intent to
Speaker 1: overwhelm the target with all that traffic and potentially either
Speaker 1: just slow it down so that it's not useful to
Speaker 1: any one who actually legitimately needs to access that server,
Speaker 1: or just shut it down entirely, like it just can't
Speaker 1: handle that traffic and it shuts down. D DOS is
Speaker 1: kind of a sledgehammer approach to an attack as opposed
Speaker 1: to like a scalpel. It's a very blunt force kind
Speaker 1: of attack. But as this Ours Technica article explains, there
Speaker 1: have been some evolutions ind DOS approaches that have made
Speaker 1: them far more dangerous than they had been previously. That
Speaker 1: the standard ways to detect and prevent de dos attacks
Speaker 1: are slowly becoming obsolete because of these new approaches, which
Speaker 1: calls for new ways to detect and respond to the attacks.
Speaker 1: There's a lot of input from the company cloud Flare,
Speaker 1: which is heavily involved in protecting clients from DIDOS attacks,
Speaker 1: so I highly recommend it. Again, that's at Ours Technica.
Speaker 1: It is titled Attackers find new ways to deliver dedosses
Speaker 1: with alarming sophistication. Once again, I have no connection to
Speaker 1: Ours Technica. I do not know Dan Goodin. I just
Speaker 1: have read lots of Dan's articles, but I've never talked
Speaker 1: to him. So it's just one that I thought was
Speaker 1: interesting and worth your time if you want to read
Speaker 1: something really interesting and certainly more than a little alarming.
Speaker 1: All right, that's it for this episode the tech News
Speaker 1: for Thursday July twentieth, twenty twenty three. I hope all
Speaker 1: of you are wealth and I will talk to you
Speaker 1: again really soon. Tech Stuff is an iHeartRadio production. For
Speaker 1: more podcasts from iHeartRadio, visit the iHeartRadio app, Apple Podcasts,
Speaker 1: or wherever you listen to your favorite shows.