AI epitomises chasing a narrow definition of progress that benefits the few (increasing profits via automation) over a holistic definition of progress that benefits the many (reducing poverty, improving health, providing meaning). It's no wonder people hate it.
The Claude Code extension in VSCode is similar enough. I used to use Cursor, but now I use VSCode+CC to take advantage of the better pricing CC offers for always-on frontier. I found Cursor's affordable "Auto" option unreliable, often wasting my time with dumb models.
For the kind of ML work I do Cursor's "Auto" was too unreliable. It would frequently try to solve relatively difficult tasks using Composer, when it should have been routing to a true frontier model. Annoyingly, doesn't tell you what model it's decided your task deserves, so I often wasted time working through a problem with it, only to realise I was on a dumb model. Then I revert all the work, switch to an expensive frontier model and pay expensive API prices to actually solve the task.
All that is to say, model selection is the main control we have over quality. Giving it up in the name of cost saving will bite you in the long run, especially when Claude Code still has such good plan pricing.
It's not like we try to fill the 30 mins, but I think we all crave a little connection with our colleagues, so make use of the time to catch up. I've worked with these same team members for over 3 years, so we are all a little invested in each others' lives by now. Obviously I'm not going to force a new team member to divulge everything about their lives, or go through my weekend in detail unless they're actually interested in chatting. It's pretty clear when someone just wants to get on with their work, rather than chat.
This isn't a company policy, it's just something I make space for in my team. There's no pressure to connect beyond the required work items.
The happy hours are only an hour a month during work hours, where we talk about stuff everyone on the team is interested in, like economics, culture and politics. Most people seem engaged and bring interesting stuff to talk about.
We also do a more formal "data blitz" in our ML team labs, where folks bring vaguely data-related topic to talk about for 10 minutes, but that requires a little prep. Those are always fun. We've had people rating diaper brands and showing their marathon training schedules.
If they don't feel like chatting they don't need to. I guess I have a chatty team. We don't always fill the 30 minutes, but we often do. It doesn't feel performative and I wouldn't waste our time if it did.
There's no consequence to skipping the happy hour but everyone shows when they can and is engaged and contributes to the conversation. We often talk about culture, politics, economics other topics most folks have a general interest in.
> I don’t need my work to provide a social life
Fair, not everyone sees work as a community, but many do. Remote culture is hard to build but it needs to allow for folks who still need human connection in their workplace.
I do this with my team. We spend more than half of our weekly 30 minute 1-on-1s talking about anything but work. That isn't written down anywhere, it's just a natural consequence of us being interested in each others' lives, and prioritizing that over "getting back" 20 minutes to do more work.
We also have a team-wide monthly "happy hour" where we bring one discussion point each, usually an interesting article. They're a lot of fun, and I appreciate my colleagues in a much more rich way than I would have otherwise.
It's so obviously important that we maintain semblance of community through live conversation in remote workplaces. I spend more time "with" my remote colleagues than I do with anyone else in my life, including my wife. The human brain does not separate cleanly into "colleagues" and "friends".
There are various levels of self deception that almost everyone subscribes to.
A pretty high level one is that our jobs are meaningfully making a positive difference in the world, when in fact, most white collar jobs are just producing bullshit to grease the corporate wheels of modern society. Most people don't like to admit that though, so we tell ourselves little lies and go along with the corporate narrative. That's what you experienced.
But it goes deeper the more truthful you try to be. Down near the bottom of this pile of self deception is that humans are making the world a better place, when in fact we're ruining the world, causing environmental damage at an unprecedented rate in geological history, all the while exhausting the readily-accessible non-renewable resources, like hydrocarbons and minerals, that'll make the chance of a better future civilization on Earth highly unlikely.
Dario and Demis have called for nationalisation at some point. They know if AI reaches what they believe its potential to be, it needs to be democratically governed. It will upend the markets, but AI already threatens to do that. It feels like wishful thinking given how entrenched we are in neoliberalism, but it makes sense.
In the mean time there are various avenues of regulation and redistribution to lessen the effects, including retraining programs, though that job creation will keep pace with job losses is a big unknown.
This is a bit of weird article. On one hand, I understand what they're getting at: AI is a transformative technology, but the people whose lives will be most transformed aren't included in the conversation. On the other hand... of course that's how it is while AI is in the hands of literal profit seeking corporations. That won't change until the labs are nationalised under a government that cares about its citizens' wellbeing. One might counter that a good corporation will listen to its customers, but that has never been the case for powerful technologies with real costs for users to not adopt them.
You lead with "Moreover, it is an optimal algorithm that minimizes state estimation uncertainty." By the end of the tutorial I understood what this meant, but "optimal algorithm" is a vague term I am unfamiliar with (despite using Kalman Filters in my work). It might help to expand on the term briefly before diving into the math, since IIUC it's the key characteristic of the method.
I love all these. I'd add Blightsight by Peter Watts to the list. It has the creepy, psychological bent of Annihilation combined with the hard science elements common to qntm's, Neal Stephenson's and Greg Egan's books.
Where I thought this was going: entering the Brand Age of AI. LLMs become commoditized, so the big labs increasingly focus on marketing and rhetoric to maintain market share. See the Anthropic spat with DoD (though I do applaud them for that, whatever their motivations).
Ditto. I kept waiting for the AI comparison. My interpretation was less agentic coding than the commodification of LLMs, forcing Anthropic and OpenAI into a pivot to focus on brand. Anthropic's spat with the DoD could be viewed through that lens: losing money on a deal to better position the brand.
Both. The same as for other materials we don't want kids to access, like alcohol. We can't expect parents to always be watching their kids. That's not how societies have ever worked.
But what I'm actually questioning in my comment above is effectiveness of the technology solution proposed at the device level.
For sure, I'm not blanket supporting age verification technology. Just saying the alternative proposed by the parent commenter isn't very reliable either.
Also, nit, but Europe has ~2x the population of the States, and definitely more cultural and linguistic diversity.