It seems like Netflix and Disney+ are taking different routes with their ad-supported tiers. Netflix went for a lower price point, aiming to grow their subscriber base, while Disney+ is focusing on increasing revenue without chasing new subscribers. What's interesting is that Disney already has a strong ad platform, which means their customers might have a better ad experience. On the other hand, Netflix needs to up their game in terms of ad technology to really make the most out of this move. It'll be intriguing to see how these strategies play out in the long run, and whether Netflix's focus on growing subscribers pays off or if Disney's revenue-centric approach is the smarter choice.
The growing dominance of industry players in AI development raises concerns about unchecked progress and misuse. As AI demands massive resources, academia has been left behind. This shift underscores the need for increased regulatory oversight and collaboration to address corporate self-regulation and to strike the right balance between AI innovation and responsible deployment.
Agreed, but right now they're only pushing papers, and what for? So companies can then move to the most favourable state?
This should be done at a federal level, and the US needs to be the global driving force behind it, ensuring all countries adopt and adhere the same principles. We need the equivalent of the International Atomic Energy Agency to manage this going forward.
Could this be even more dangerous than a nuclear bomb?
WiSwarm's fresh take on data prioritization for time-sensitive robotic and IoT applications could seriously shake things up, particularly in areas like drone-assisted disaster relief and smart city management. That said, we should keep an eye on potential issues related to data quality, accuracy, centralized processing power, and scalability. As IoT continues to weave its way into our daily lives, it's important we thoroughly examine WiSwarm's impact on data integrity, privacy, and the overall performance of interconnected networks.
It seems like many of the TinyML use cases are hidden or somewhat dull, making it difficult to get people excited about it. Do you think there are ways to make TinyML more exciting and appealing to a wider audience? How can we better showcase the potential of TinyML and its ability to bring more privacy to IoT and give everyday products superpowers?
How about just being able to run a home assistant with AI support to reprogram the home assistant, without having to spend a lot more electricity? They don’t have to have superpowers to be useful.
The clear use-case for it is mechanical control and feedback. But it seems that every robot has enough tiny problems that you can justify a larger CPU anyway. I too am having a hard time being excited about it.
How do you handle the limitations of graceful restarts when dealing with UDP-based protocols like HTTP/3, where there is not even a concept of a listener socket? And is there a way to carry existing state to a new process to avoid these limitations?
Would be nice if the intro video would demonstrate how it works. Easier to show, i.e. make the intro a fake meeting call with the minutes summarising your tool's capabilities.
Nice project! I was hoping for a tool that does something like that. But how will it deal with the context needed to keep in larger projects? Speed and cost will be an issue too? You could rack a millions of tokens in a workday.
Glad you liked it! Currently, context size is an issue. The user must clear the conversation when the context limit is reached. Knowing that I added basic memory access commands so GPT-4 may store some context between sessions. To reduce the context usage I also defined a system prompt that incentivizes selecting code ranges, not entire files. With this, GPT-4 is able to solve medium-complexity tasks, including implementing commands in this extension itself.
For the future I expect GPT-4 with 32k tokens will greatly improve this extension capabilities. Also, I am looking into LangChain to reduce conversation length, define goals and employ a better memory solution.
What are some of the edge cases that need to be handled for the first and last points in a path when using the Screen-Space Projected Lines approach for rendering lines in 3D space?
That is their right, of course. Could this be a sign that it is tough in the SWE job market at the moment?! Usually moving on from Google would have been a non-issue to find a new job.
>Could this be a sign that it is tough in the SWE job market at the moment?!
No. There's plenty of companies hiring everywhere. SWEs will not be unemployed.
It's probably tough only if you expect to still make post-pandemic boom Google TC and perks at Google WLB.
Which is why it's wise to avoid lifestyle inflation. If you ever land a lucrative job during a boom, don't expect it to last forever and start buying Ferraris and max out your loans. Be humble and wise with your spending so you can whither any storm.
The cost of a sports/luxury car seems reasonable, esp for a high income earner, maybe 30-50% more than something more modest. But the upkeep is literally insane. A brake job on an Audi can cost 3-4x that of a Honda. Oil changes can be 2-3x.
A lot of modern sport cars are currently going up in value because new cars are either unavailable in the short term or not satisfying enough to the car enthusiast crowd.
In general used car prices/trade-ins were sky high last summer because of lack of new car availability. Not sure what it's like currently. My sense was that supply chain woes had eased somewhat.
I don't think so. The article says that this about the union being ignored. At this point it seems like a European ethos vs American. The Europeans are standing up for the collective right unions. It think this gets lost on Americans.
