evilantnie

I feel like everyone in this reply chain is looking at this from a different angle of Fast, Good, Cheap. Pick two.

If we want parents to be accountable, then these platforms need to provide better tools to enable parents to do so. It is impossible to monitor the entirety of your child's behavior online through any of these platforms today. They are their own person, they make their own choices, and those choices are heavily influenced by a world the parents have increasingly less influence over, especially as they grow older.

On the flip side, I do think we should also hold companies more accountable for this. We collectively prevented companies from advertising tobacco to minors through regulation with a pretty massive success rate. These companies know how harmful social media can be on youth, and there is little to no effective regulation around how children learn about these platforms and get enticed into them.

There are infinite things worth doing, a machines ability to actually know what's worth doing in any given scenario is likely on par with a human's. What's "Worth doing" is subjective, everything comes down to situational context. Machines cannot escape the same ambiguity as humans. If context is constant, then I would assume overlapping performance on a pretty standard distribution between humans and machines.

Machines lower the marginal cost of performing a cognitive task for humans, it can be extremely useful and high leverage to off load certain decisions to machines. I think it's reasonable to ask a machine to decide when machine context is higher and outcome is de-risked.

Human leverage of AGI comes down to good judgement, but that too is not uniformly applied.

I think this particular exploit crosses multiple trust boundaries, between the LLM, the MCP server, and Supabase. You will need protection at each point in that chain, not just the LLM prompt itself. The LLM could be protected with prompt injection guardrails, the MCP server should be properly scoped with the correct authn/authz credentials for the user/session of the current LLMs context, and the permissions there-in should be reflected in the user account issuing those keys from Supabase. These protections would significantly reduce the surface area of this type of attack, and there are plenty of examples of these measures being put in place in production systems.

The documentation from Supabase lists development environment examples for connecting MCP servers to AI Coding assistants. I would never allow that same MCP server to be connected to production environment without the above security measures in place, but it's likely fine for development environment with dummy data. It's not clear to me that Supabase was implying any production use cases with their MCP support, so I'm not sure I agree with the severity of this security concern.

The dinosaurs didn't create the asteroid that hit them, so they never had the chance for a real debate.

I don’t think the real divide is “doom tomorrow” vs “nothing to worry about.” The crux is a pretty straightforward philosophical question "what does it even mean to generalize intelligence and agency", how much can scaling laws tell us about that?

The back-and-forth over σ²’s and growth exponents feels like theatrics that bury the actual debate.

Ironically, this article highlights multiple times how successful Microsoft has been at boosting efficiency within the oil and gas industry that it's nearly an advertisement for Microsoft.

STIR/SHAKEN doesn't prevent spoofing. It can verify in certain cases when a call is not spoofed but it's fairly limited and almost entirely mobile-to-mobile phone calls. It requires IP based network connectivity end-to-end, which just isn't possible in the US. If a call gets routed through a rural network and switches back to TDM, it will drop all STIR/SHAKEN data. It will still take years for US infrastructure to be entirely IP-based. Robocallers sign their calls with STIR/SHAKEN just fine, the originators do this for them, so it's not going to be a strong deterrent in my opinion.

Devices support attestation level A display (green or grey check marks in your call logs designate this). If you haven't seen that check mark, then you probably haven't seen many A-level attested calls to your device. As far as device manufacturers go, they only care about A-level attestation, which makes sense as it has full traceback capability.

Just to help not spread misinformation, the 12 year old was released as he was a passenger and police believe he was forced by the driver (his brother) into the car.

The 13 year old driver was not released and will remain in jail until his trial.

Copilot is a lossy compression algorithm when applied at scale, I would expect some degradation in code quality if not applied appropriately. It's still a useful tool, but just like image and audio compression, a human needs to give the final output some last looks to ensure an acceptable out come.

"best" is subjective, but I do think the industry will eventually converge onto an architecture that is significantly more cost effective than current state of the art. Regardless of who is first to market, everyone is incentivized to continue down this path with their research on improving LLM performance.

TTS and STT models have decent support for streaming in chunks, but the accuracy drops the smaller the chunk size. Current state of LLMs are pretty limited in their ability to handle streaming inputs due to attention window constraints. There is some emerging research into attention sinks and caching initial tokens that look promising. I don't think we're quite there yet though.

QA has always been about risk management. There are multiple ways to manage risk, and some of those ways can be more cost effective to a business. As software shifted towards SaaS offerings, deployments (and rollbacks) became quicker, customer feedback loops also got lightning fast. Team's can manage the risk of a bug more efficiently by optimizing for mean-time-to-recovery. This muscle is not one that QA teams are particularly optimized for, thus their effectiveness in this new model was reduced. I've found that holding on to QA function in this environment can severely dilute the ownership of quality as a requirement from engineers.

QA is still extremely valuable in any software that has long deployment lead times. Mobile apps, On-Prem solutions, anything that cannot be deployed or rolled back within minutes can benefit from a dedicated QA team that can manage the risk appropriately.

From what I'm reading here, the company misled "investors" by attaching the NFT to ownership in the company, which would be considered a security.

"The order finds that Impact Theory encouraged potential investors to view the purchase of a Founder’s Key as an investment into the business, stating that investors would profit from their purchases if Impact Theory was successful in its efforts."

When I purchase a baseball card, I do not have the expectation that there is any additional value attached to the baseball card beyond what the collector's market will pay.

You've linked to ping/ICMP statistics, TCP is a more common use case and thus tends to be more representative of real-world applications. 100ms is a fairly realistic 90th percentile in my experience, 150ms could be in the 95th.

This sounds weird to me, I've paid for quite a few large construction projects and they are always fixed-bid contracts. I've never borne the cost of a mistake made by contractors. Everything that has additional cost is strictly controlled by change order requests, to the point of being extremely annoying. Maybe it's personal preference for fixed-bid contracts, but I've never heard of a large hotel, hospital, or other large contract be time-and-material based.

It is, but Github's terms do not allow your code to be shared with others. Although ChatGPT represents that it does not retain information provided in conversations, it does “learn” from every conversation. There is currently little reassurance as to how those "learnings" are leveraged outside of your own usage.

There is a huge difference between the creative content industry and commodities such as fabrics production. While there are some lessons to be learned from that history and the current situation, I don't think you can compare apples to apples. The results are unlikely to be the same in my opinion.

I don't think you can leverage AI in Hollywood for profit on blockbusters without highly trained artists in the mix. It is possible that it could impact the long-tail of b-movies out there, but I think audiences will be able to see through this. I don't know how sabotage will work in this case either.

The article skims over the details from the FCC, in this situation Twilio is guilty by association. They are the CPaaS provider for a company called PhoneBurner, which in-turn provides services to a Mortgage company (MV realty) who is the primary offender of the robocalls.

The FCC is taking a firmer stand and threatening those that support robocalls all the way down the chain. All CPaaS providers need to do a better job managing their customer vetting processes.

They changed what It was!

I'd be curious if you feel the same way in a year or so. When I first got into VR I felt very strongly it was the future, but that novelty wore off over the course of a year. I go back every few months to catch up on experiences I've missed and try out new tech, but the novelty has still worn off.

VR is not a daily use experience for me, and I assume for a lot of consumers, but it is still amazing.

This article inadvertently touches on complexity theory, which is something I've recently become interested in from a management perspective. In complexity theory, organizations are viewed as complex adaptive systems https://en.wikipedia.org/wiki/Complex_adaptive_system which are dynamic networks of interactions, much like this article is describing.

It's been an interesting thought exercise to ignore typical management styles focusing on command and control structures, and shifting to holistic view of the organization and the networks that support its function. i.e. if you want to understand success of your top performers, you have to consider the system they operate within and how it enables their success. I think that relates to the point of this article, and I really enjoyed connecting the dots.

Carbon offsets are a financial instrument, which is very different than an approach that treats CO2 as a waste product. By nature trying to solve this via a financial instrument likely won't motivate anyone, it's just a way for organizations to play hot potato and literally pass the buck. However, if we were to treat CO2 emissions as a waste product, it would likely have more restrictive industry regulation around how organizations are required to manage their C02 waste by products.

Apple's market share when it comes to streaming video is not as dominant as it is for mobile apps. Samsung, Android, and WebOS platforms out-share them by quite a bit, Amazon had already established their app in those markets, along with the success of the firestick.

This was all about subscriptions, and the customers weren't watching or had stopped watching on apple devices in 2016/17, so Apple was willing to concede the rev share % to retain subscriptions that started on their platform. Now Apple gets to count those numbers as subs, even if they aren't watching on Apple devices anymore.

Who are these normal people you're referring to?

Why is it a scary concept to them?

Why should the message be diluted to reduce normal people's fears?

It's explicitly demanding an alternative system to one that has for decades instilled fear of violence towards Black folks.

I support the slogan, and the weight behind it. The intention is to spark discomfort in normal people, change won't happen when normal people feel comfortable.

I don't know if it's a fair takeaway to consider the decline in non-streaming music was unaffected by streaming that early on. Napster launched in 1999 as a first iteration of what could be considered a streaming service at the time. This chart doesn't represent that impact at all since it's focused on revenue, but timing wise I think there could be correlation.

I was also surprised by this when I first saw it, but if you read the reasoning behind the ending of the program, it kind of makes sense. It sounds like they are just switching their focus.

The emissions check program is aimed at carbon monoxide, nitrogen oxides, volatile organic compounds, and particulate pollution. Properly functioning emissions systems ensure a vehicle operates efficiently, but the effect on a car or truck's overall greenhouse gas emissions is fairly small - and it is greenhouse gases (primarily carbon dioxide) that are driving climate change.

Vehicles are still the largest source of carbon pollution in Washington. We are working to change that by making sure new cars are more efficient than old ones, supporting zero-emission vehicles and cleaner fuels, and advancing transit, ridesharing and other alternatives to single occupancy vehicles.

we expect air quality to continue to improve as older vehicles are replaced with newer, cleaner cars. Ecology will continue to monitor air quality conditions throughout Washington. If we see any reasons for concern, we will certainly take action.

http://www.medievia.com/ was mine, and it's still chugging along since '92, I played all through high-school, but then WOW came along. Before I learned about the tintin mud client, I had actually memorized key strokes to get around the map, good times.

I don't see the comment you're referring to, but McBride was quoting one of the authors of the study. Technically this isn't "spin", Toxic Masculinity and Hegemonic Masculinity are both fields of study in psychology having to do with promotion of dominance and violence. I think both fields influenced this study. It looks like they developed a Parent-Child-Conflict scale that included spanking, hitting, or threatening physical harm to measure some of this, but the study is much more broader than just this.

So, we are living in a simulation?