This week we talk about React hooks, CloudFlare caching, SVB’s fall from grace, AI winter, generated AI aesthetics, non-linear workdays, and how to leave work early.
People like signals because signal-based components are far more similar to class components than to function components with hooks.
I think React made a mistake in that they only provided a few hook primitives, and expected developers to compose their own use cases, or fallback on hard-to-locate 3rd party libraries. Many developers struggled, and the overall developer experience was and still is frustrating.
Signals do solve a common use case that React ignored, but also they’re an incremental improvement that adds another primitive, without solving the core problem and raising the level of abstraction.
But more specifically, the same playbook that sold you React hooks as the solution to all problems is now selling signals and/or “not React”. It’s the same grievance-based marketing that funnels attention to the next ultimate solution. Fool me once …
I’m increasingly over the “React Hooks were a mistake” genre of takes. Not everyone’s brain has to work the same way. If hooks are weird to your brain or seem like an unhelpful paradigm, don’t use them. Or don’t use React. There are great alternatives to it now! But there’s no need to claim it’s wrong and bad for anyone to use. Go solve real problems with whatever tool or framework makes you most productive. #reactjs #webdevelopment
2 bucks a day 😲 But this has taken nearly 16M requests off my origin service over this period of time so I haven't paid for the Azure Function execution (which is cheap) nor the egress bandwidth (which is not cheap).
Proud to be on @Forbes' annual ranking of America's Best Banks for the 5th straight year — Mar 6, 2023
Morning Brew has a good explainer of how SVB went from 60 to 0 in less than 48 hours (you can’t even get a bank wire transfer to happen that fast.)
I, having 0 years of experience in the banking industry and therefore being totally qualified to have an opinion in this matter, explain why the sky isn't falling.
And if you want to be nice, this is the weekend to hug a CFO.
Why AI is Harder Than We Think I agree with some of the main points: progress in AI is not linear, AGI is still far out, and hype always meets a moment of reckoning.
But this time it’s different because … unit economics. I wrote a whole thread about it, the gist of it:
1980’s tech couldn’t possibly run GPT-3 to summarize an email, and if it could, it would cost you $1K (or some such amount)
2020’s tech can summarize an email in 5 seconds for $0.01, and enough people will pay $20/month to get their inbox under control
Philosophers ask “does next-token prediction qualify as intelligence?”, while businesses ask “can I charge more than it costs to serve?”
LLMs don’t have to be perfect, just good enough and cheap enough to reach enough customers who feel that way and are willing to pay more than it costs to serve them
All of these are true now, just look at this chart:
When Google integrates GPT into Google Docs, they will Sherlock a lot of startups. They probably won't do it as well, but hard to compete with free when don't even have a way to benchmark GPT against each other. (Anyone working on that? DM me)
Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence So much research (esp in software development) is conducted in lab settings and doesn’t replicate in the real world. So I appreciate this research includes a follow-up section, where they review whether people keep using the technology, and what’s their experience away from a controlled setting:
33% of former treatment group participants have used ChatGPT in their job in the past week, relative to 18% of control group participants. Restricting to workers who had not previously used ChatGPT when they participated in our main experiment, 26% of treated and 9% of control workers are now using ChatGPT in their jobs (p-value on difference 0.048). Users give it an average usefulness score of 3.65/5.00, somewhat lower than in our main experiment, likely owing to the greater length and complexity of real-world tasks. The range of tasks they report using it for is broad: generating recommendation letters for employees, responding to customer service requests, brainstorming, search-engine requests, rough-drafting emails, and so on. Respondent
Also, this resonates with me:
If ChatGPT is especially helpful to those with poor writing and communication skills relative to their other skills, it could have major labor market implications by expanding the available occupational choices and raise the earnings of individuals with strong idea-generation skills who struggle to effectively get those ideas onto paper.
The Impact of AI on Developer Productivity: Evidence from GitHub Copilot In contrast, this article only measures performance under ideal/synthetic settings. It's a micro-benchmark, and I won't draw conclusions about real life experience, but even a 5% gain (vs 55%) is 2 hours out of the week.
oh no we made a matrix too big and multiplied it too many times and now it has feelings
@Roland Meyer This thread (with images) captures the new aesthetics well:
Now that the DALL-E has been successfully midjourneyfied, it is becoming apparent that instead of simulating all possible ›styles‹, AI is fostering the emergence of a distinct visual style, born out of popular aesthetic preferences dominating platforms like DeviantArt
1/6
Most AI-generated images — and I’m being generous here — are not worth the bites. Only a select few get published and re-shared. It’s people who select which images will be shared and what aesthetics will come to define AI-generated art.
MidJourney captured that preference early on, StableDiffusion and DALL-E are slowly adapting to match that aesthetic. Evolutionary pressure applied to text2image models.
The gaze that determines this aesthetics is determined by early adopters of and it will come to define 2023 aesthetics like skeuomorphism, round buttons, and Corporate Memphis years before.
What should we call it?
Can AI perfect the IPA? I know some people who will find this headline a combination of two disturbing trends
“People aren’t stupid” may always be a radical idea. There will always be people doing stupid stuff, and it will always be tempting to assume that stupid actions = stupid people. It’s hard to imagine how naive realism could disappear, or how we could bridge the psychological distance between each person and the public.
In the modern-day vernacular, people often refer to a criminal case “being thrown out”. Obviously, this is little more than a figurative expression. Cases aren’t actually thrown out, in the literal or physical sense. Nevertheless, in the specific circumstances of this case, the Court is inclined to actually take the file and throw it out the window, which is the only way to adequately express my bewilderment with the fact that Mr. Epstein was subjected to an arrest and a fulsome criminal prosecution. Alas, the courtrooms of the Montreal courthouse do not have windows.
Other gems:
Since I’m hesitant to draft an entire decision in bold and caps-lock characters, I offer the following observations instead.
…
At trial, there is no evidence before me suggesting these young children form a criminal or terrorist organization.
…
The comment further showed that the complainant’s account is overly dramatic and theatrical. This deplorable Laval reference is worthy of an eye roll that could sever both optical nerves.
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This week we ask who's responsible for technical decisions, dig into the origins of spaghetti code, discover a new dopamine loop, talk a lot (too much?) about generative AI, and wrap it up with a
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