SendGrid phishing emails are some of the best phishing emails. I get emails that there's elevated error rates on an API (`/v1/send`). Looks very legit, good design, reasonable call to action, some urgency which makes me want to click. They know from MX records I send email with Sendgrid, so it's well targeted. Easy catch when I see the domain, but other than that it's the best I've seen in years.
Exercising can help. It's not bad advice or inappropriate to suggest it. People shouldn't suggest it as if it's a cure all and certainly shouldn't suggest you just need to buck up, but the study is showing it can really help.
Context: I'm "using" SSRIs, talk therapy, psychotherapy, strength training and endurance training -- all in parallel right now.
It can be inappropriate depending on where the person is, when I was diagnosed I could barely get out of bed. Feels a bit like telling an anorexic person to eat something.
> It’s a bit strange how anecdotes have become acceptable fuel for 1000 comment technical debates.
Progress is so fast right now anecdotes are sometimes more interesting than proper benchmarks. "Wow it can do impressive thing X" is more interesting to me than a 4% gain on SWE Verified Bench.
In early days of a startup "this one user is spending 50 hours/week in our tool" is sometimes more interesting than global metrics like average time in app. In the early/fast days, the potential is more interesting than the current state. There's work to be done to make that one user's experience apply to everyone, but knowing that it can work is still a huge milestone.
At this point I believe the anecdotes more than benchmarks, cause I know the LLM devs train the damn things on the benchmarks.
A benchmark? probably was gamed. A guy made an app to right click and convert an image? prolly true, have to assume it may have a lot of issues but prima facie I just make a mental note that this is possible now.
This also leads to the unreasonable effectiveness of LLMs. The models are good because they have thousands of years of humans trying to capture every idea as text. Engineering, math, news, literature, and even art/craftmanship. You name it, we wrote it down.
Our image models got good when we started making shared image and text embedding spaces. A picture is worth 1000 words, but 1000 words about millions of images are what allowed us to teach computers to see.
Is doing dozens of back and forth to explain what we actually want, while the model burns down inordinate amount of processing power at each turn, a model of efficiency or effectiveness ?
It might be convenient and allow for exploration, the cost might be worth it in some cases, but I wouldn't call it "effective".
Regarding effectiveness, LLMs are in a class of their own wrt. their capabilities for general language processing and basic few-shot reasoning.
This also invalidates the "efficiency" question, since the cost of doing those tasks without LLMs is infinity (i.e. you can pay as much as you want, a dolphin is never going to replace the LLM).
Alternatively block it from the internet at the router, or connect to a LAN-only subnet. Keeps the benefits of local AirPlay, Chromecast, and HomeKit without being able to phone home.
I too am irritated by their software but they do make nice hardware. I’d have their headphones if I trusted their software, the hardware is perfect IMO. Open and upgradable is not really their forte though.
Offline smart TVs are great. As long as they support wake over CEC, they are close enough to a dumb display connected to an Apple TV.
I let my latest LG TV on the network, but block internet access at the router. HomeKit integration (Siri turn off tv), Chromecast, Airplay, and other local services all work, without the ability for it to phone home.
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