Comment Cue all burglars (Score 1) 31
I'm a burglar, and I will suffer irreparable harm if the law is not changed to make burglary legal.
Comment Re: solid state (Score 1) 131
Speaking of outlier arguments that depend on a false premise on top...
Comment Re: solid state (Score 2) 131
Same. I have a 185 mile round trip commute that is served perfectly by my EV. We do 100% of our around-town driving in it, day trips an hour+ away, 99.9% of our driving is served by the trusty EV. I have gone on ~600 mile trips that have required two charging stops, and you know what, it's nice to take a 25 minute break every few hours anyway. Plug in, go grab a snack, sit at the picnic tables, enjoy my meal, walk around, relax, then go another leg. 99% of the arguments against EVs are specious and rely on that one outlier use case that is not served well by an EV.
Comment Re: Diminishing returns (Score 1) 70
DDR6 isn't any faster than DDR4. The only real difference is that DDR6 is less reliable.
Comment I learned a lot when I got mine (Score 2) 66
I stayed in school for a couple of years to get my MSEE after getting my bachelor's. It was like being in Montessori school again and I loved it. It was the first time I had really manage my time over the long stretch - not just to get through this week's test, but to make my overall project successful. My advisor was more or less hands off, but available if I got stuck. Otherwise, it was up to me. That was 25 years ago. About 5 years ago I made the transition to leadership roles to be that advisor to the new guard, but I still value an MS if it was done with the right intent. A lot of colleges today will throw you an MS if you just take a few extra classes, but when I see a well-planned thesis that the candidate can demonstrate true understanding in an interview, it tells me (along with many other things) that they can manage goals, timelines, requirements, and do the validation work to tie it all up. It's nice when I don't have to spend their first 2 years at the company developing those skills in them.
To me the whole point of the MS is to give you something to figure out on your own and make you learn how to manage it. Taking a bunch of classes only makes you better at getting through this week and temporarily memorizing enough formulas to get through a final. There's little true understanding in that.
Comment People buy Honda because they're boring (Score 1) 157
People buy Honda because they're simple, boring vehicles that are easy to learn to drive and maintain. They don't have complicated whizbang features and are very appropriate for people who don't want to have to get a rocket surgery degree to own.
An EV is an incredibly scary proposition to Honda's demographic. It's no surprise at all that their EV venture fell flat.
Comment Re: If it's free, you are the product (Score 2) 99
The absence of the delete feature and unlimited storage was prompted by grants from law enforcement. Email stored for over 6 months is considered "abandoned" and does not require a warrant for law enforcement to obtain and read. Another feature of abandoned emails is that attorney-client and spousal privilege are set aside because clearly no one cares about "abandoned" material.
Comment Re: All according to plan. (Score 0) 214
So, you make your EV buying decision based on what connector it has? Why do you care so much about a connector?
Comment Re:Not loving it (Score 1) 46
Jet Engines are as efficient as the steam turbine generators used at power plants.
Comment Is 250MM punitive at all for Apple? (Score 1) 37
That's something like 47 minutes of profit for the company. Is it really going to dissuade bad behavior in the future? I think not.
Submission + - The Audio Industry Is Grappling with the Rise of 'Podslop' (bloomberg.com)
An anonymous reader writes: Welcome to the modern era of podcasting in which thousands of new shows are released into the world every day with a sizable portion likely being AI-generated. Figuring out exactly which ones fall into that growing category is becoming more difficult just as the industry is starting to take this issue seriously. In only the past month or so, Amazon launched a feature that explains a product by generating a quasi-podcast, complete with co-hosts talking to each other and taking questions from users. Shout out to Business Insider reporter Katie Notopoulos for spotting this (and, naturally, demoing it with an adult diaper rash-cream). Not long ago, Nicholas Thompson, chief executive officer of the Atlantic, noted “podslop” dominated his Spotify search results when he typed in the word “Sora.” This was around the time that OpenAI shut down its user-generated, AI-content-only app.
[...] All of which raises some big, difficult questions. For one, what should the listening platforms do about this incursion? As of right now, Apple Podcasts requires creators who generated a “material portion” of their show using AI to disclose it. The platform also bans misleading or deceptive content. Spotify hasn’t published any specific guidelines around AI, though it maintains general rules around dangerous and misleading content. Where this conversation gets even trickier is when it comes to money. Many of these podcasts are hosted on at least one free service that allows programs to opt into their ad marketplace with zero barrier to entry, meaning these shows (and the hosting service) profit off every listen or download. Spreaker, a company owned by iHeartMedia, is the primary one to watch here. Though it tells users to disclose when they rely on AI, it still allows those shows to opt into its programmatic ad marketplace, which pays creators 60% of the revenue generated by the ads placed in their shows. It stands to reason that most of these thousands of shows don’t reach many people. But in the aggregate, the ears and dollars could add up. Are the advertisers on board with being next to AI-generated content, some of which might be deemed “slop?”
[...] All of which raises some big, difficult questions. For one, what should the listening platforms do about this incursion? As of right now, Apple Podcasts requires creators who generated a “material portion” of their show using AI to disclose it. The platform also bans misleading or deceptive content. Spotify hasn’t published any specific guidelines around AI, though it maintains general rules around dangerous and misleading content. Where this conversation gets even trickier is when it comes to money. Many of these podcasts are hosted on at least one free service that allows programs to opt into their ad marketplace with zero barrier to entry, meaning these shows (and the hosting service) profit off every listen or download. Spreaker, a company owned by iHeartMedia, is the primary one to watch here. Though it tells users to disclose when they rely on AI, it still allows those shows to opt into its programmatic ad marketplace, which pays creators 60% of the revenue generated by the ads placed in their shows. It stands to reason that most of these thousands of shows don’t reach many people. But in the aggregate, the ears and dollars could add up. Are the advertisers on board with being next to AI-generated content, some of which might be deemed “slop?”
Submission + - Cisco releases open-source 'DNA test for AI models' (scworld.com)
spatwei writes: Cisco released an open-source tool to trace the origins of AI models and compare model similarities for great visibility into the AI supply chain.
The Model Provenance Kit, announced Thursday, is a Python toolkit and command-line interface (CLI) that looks at signals such as metadata and weights to create a “fingerprint” for AI models that can then be compared to other model fingerprints to determine potential shared origins.
“Think of Model Provenance Kit as a DNA test for AI models,” Cisco researchers wrote. “[] Much like a DNA test reveals biological origins, the Model Provenance Kit examines both metadata and the actual learned parameters of a model (like a unique genome that comprises a model), to assess whether models share a common origin and identify signs of modification.”
The tool aims to address gaps in visibility into the AI model supply chain. For example, many organizations utilize open-source models from repositories like HuggingFace, where models could potentially be uploaded with incomplete or deceptive documentation.
The Model Provenance Kit, announced Thursday, is a Python toolkit and command-line interface (CLI) that looks at signals such as metadata and weights to create a “fingerprint” for AI models that can then be compared to other model fingerprints to determine potential shared origins.
“Think of Model Provenance Kit as a DNA test for AI models,” Cisco researchers wrote. “[] Much like a DNA test reveals biological origins, the Model Provenance Kit examines both metadata and the actual learned parameters of a model (like a unique genome that comprises a model), to assess whether models share a common origin and identify signs of modification.”
The tool aims to address gaps in visibility into the AI model supply chain. For example, many organizations utilize open-source models from repositories like HuggingFace, where models could potentially be uploaded with incomplete or deceptive documentation.
Comment Phew! Thank god there are alternatives (Score 1) 30
Man I'm really glad my favorite BBS has a web search gateway. I just upgraded to a 19.2k modem so I'm ready to keep blazing the trail on the world wide web! Now what was the name of that IRC server...
Submission + - A 22-Year-Old Dropout Just Reverse-Engineered The World's Scariest AI (forbes.com)
ZipNada writes: When Anthropic introduced its powerful new model, Claude Mythos, this spring, companies and countries freaked out. The general-purpose model, its creators claimed, could discover software vulnerabilities that no one knew existed.
Rather than release Mythos to the world, the company gave it to cybersecurity experts at major companies that build or maintain critical software infrastructure and told them to use it to find and fix bugs before Anthropic unleashed it on the world.
But less than two weeks later, 22-year-old developer Kye Gomez made educated guesses about the core design that makes Claude Mythos so powerful and published OpenMythos, a public project that approximates Anthropic’s breakthrough. Gomez’s code raced through the research community like a prairie fire.
This story has several startling implications: if a self-taught developer can reverse-engineer the structural innovation of a multi-billion-dollar lab in a matter of days, then the proprietary moat around AI architecture may already be gone.
Rather than release Mythos to the world, the company gave it to cybersecurity experts at major companies that build or maintain critical software infrastructure and told them to use it to find and fix bugs before Anthropic unleashed it on the world.
But less than two weeks later, 22-year-old developer Kye Gomez made educated guesses about the core design that makes Claude Mythos so powerful and published OpenMythos, a public project that approximates Anthropic’s breakthrough. Gomez’s code raced through the research community like a prairie fire.
This story has several startling implications: if a self-taught developer can reverse-engineer the structural innovation of a multi-billion-dollar lab in a matter of days, then the proprietary moat around AI architecture may already be gone.
Submission + - Physicists just found a tiny flaw in time itself (sciencedaily.com) 1
alternative_right writes: Physicists are rethinking one of quantum mechanicsâ(TM) biggest puzzles: how fuzzy possibilities become definite reality. New research suggests that spontaneous âoecollapseâ processesâ"possibly linked to gravityâ"could subtly blur time itself.
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It is masked but always present. I don't know who built to it. It came before the first kernel.
