Technology
News community around technology, social media platforms, information technology and governmental policy surrounding it.
What doesn't fit here?
The core of the story has to be technology focused.
- If article mentions "AI" in a sentence and then talks about business economics that doesn't make it tech news.
- Gaming is too many layers removed from technology. There are many dedicated communities that are a better fit for it.
- Transporation is too many layers removed from technology. EVs while use many cool technologies have many dedicated communities that are a better fit for it.
- Entertainment is too many layers removed from technology. While sometimes it can fit here, business or cultural aspects of it are a better fit for dedicated communities.
- Cybersecurity. While it heavily focuses on technology, most of the time it's too technical for most people who are not already invested in it. Should be posted in a dedicated communities unless it has broader connection to other tech areas.
Post guidelines
Title format
Post title should mirror the news source title. If you don't like the title of article, look for an alternative source instead of editorializing it.
URL format
Post URL should be the original link to the article (even if paywalled) and archived copies left in the body. It allows avoiding duplicate posts when cross-posting.
[Opinion] prefix
Opinion (op-ed) articles must use [Opinion] prefix before the title. Opinion articles refer to articles that their publisher doesn't explictly endorse.
Country prefix
Country prefix can be added to the title with a separator (|, :, etc.) if the news is from a local publisher who doesn't clearly mention the country.
Rules
1. English only
Title and associated content has to be in English.
2. Use original link
Post URL should be the original link to the article (even if paywalled) and archived copies left in the body. It allows avoiding duplicate posts when cross-posting.
3. Respectful communication
All communication has to be respectful of differing opinions, viewpoints, and experiences.
4. Inclusivity
Everyone is welcome here regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, or sexual identity and orientation.
5. Ad hominem attacks
Any kind of personal attacks are expressly forbidden. If you can't argue your position without attacking a person's character, you already lost the argument.
6. Off-topic tangents
Stay on topic. Keep it relevant.
7. Instance rules may apply
If something is not covered by community rules, but are against lemmy.zip instance rules, they will be enforced.
Companion communities
!globalnews@lemmy.zip
!interestingshare@lemmy.zip
Icon attribution | Banner attribution
If someone is interested in moderating this community, message @brikox@lemmy.zip.
view the rest of the comments
Thanks, interesting thoughts. I am trying to understand agentic AI and its potential uses and security risks better. I am also a bit hesitant to let it loose on my laptop, even if you sandbox the thing. I was also amazed how all our executives were pushing us to use AI for everything, without really trying to figure out legitimate use cases that will move the needle and without considering the massive potential costs. Then some of our agents suddenly got switched off, when token budgets were used up faster than expected.
The S in "agentic" stands for security!
I almost forgot: The reason why "business leaders" want to see AI everywhere is because they think it'll be just like the adoption of every other technology to this point: It gets cheaper over time (not always better, but usually so).
The assumption is that if they "beat their competitors" to be the first ones using AI efficiently, they'll utterly destroy them (economically; they won't be able to compete). It's a very bad assumption.
So far, "Big AI" is getting better but at costs that scale geometrically with the amount of "better". That is: You can improve reliability (e.g. reduce hallucinations, increase accuracy, improve outputs in various ways, etc) but only by drastically inflating the cost and at reduced speed and efficiency.
We're starting to learn that LLMs need about two generations of hardware advances before they're going to be cost efficient for the types of "human productivity enhancement" that business leaders want. It's only affordable now because "Big AI" is subsidizing the costs, trying to get customers hooked. The assumption being that if they're hooked on AI, they'll be able to raise prices to reflect actual costs. Just like the business leaders, this is a very bad assumption.
Instead, what's going on is that the open weights AI models are starting to get "good enough" for most tasks (that you'd want to use them for, e.g. coding or agentic automation stuff). That means that all the billions and billions being spent by Big AI is just building up debt that will never be repaid and having this side effect of using up all the chip/memory capacity in the entire world.
It's an absurd situation and the world will eventually look back on this time like we do the dotcom era.