I wonder how this intersects with their interest in "unbiased" models. Scare quotes because their concept of unbiased is scary.
"unbiased", in the world of realpolitik, means "biased in a manner to further my agenda and not yours".
Readit Newsrayval commented on US AI Action Plan ai.gov/action-plan... · Posted by u/joelburget
rayval commented on Collaborative, agent to agent scenarios google.github.io/A2A/#/... · Posted by u/tarasyarema
After the release yesterday, I think it's an interesting move from Google, and specially the sample code they have in the repo.
Seems like a natural move after the MCP release, and I'm curious to see how many A2A new tools will appear in the next weeks, has anyone already started working on a Python library to implement the A2A interface?
They say that MCP can be used in conjunction, but I'm not sure if this actually makes the type of interaction move from the MCP (tool) level to the agent level.
Also, the auto-discovery with the well-known/agent.json I think it's something that is missing on the MCP world (?).
What do you think about it?
A lot of discussion about A2A here:
https://news.ycombinator.com/item?id=43631381
rayval commented on The impact of competition and DeepSeek on Nvidia youtubetranscriptoptimize... · Posted by u/eigenvalue
I think it's worth double clicking here. Why did Google have significantly better search results for a long time?
1) There was a data flywheel effect, wherein Google was able to improve search results by analyzing the vast amount of user activity on its site.
2) There were real economies of scale in managing the cost of data centers and servers
3) Their advertising business model benefited from network effects, wherein advertisers don't want to bother giving money to a search engine with a much smaller user base. This profitability funded R&D that competitors couldn't match.
There are probably more that I'm missing, but I think the primary takeaway is that Google's scale, in and of itself, led to a better product.
Can the same be said for OpenAI? I can't think of any strong economies of scale or network effects for them, but maybe I'm missing something. Put another way, how does OpenAI's product or business model get significantly better as more people use their service?
In theory, the more people use the product, the more OpenAI knows what they are asking about and what they do after the first result, the better it can align its model to deliver better results.
A similar dynamic occurred in the early days of search engines.
One American user, who identified themselves as “non-binary” on RedNote, was censored after publishing a post on Tuesday asking if the platform welcomed gay people. The post was removed within hours, the user told CNN [0]
The next day, they uploaded a new post saying they will quit the platform over the decision but was soon on the receiving end of homophobic comments, with some users accusing them of cultural imposition.
A Chinese user suggested that he try covering his nipples, as Chinese social media platforms generally impose restrictions on displaying them when it is perceived as sexually suggestive.
A few RedNote users also noted that posts about the Japanese anime My Hero Academia, which faced censorship in China since 2018 due to controversial references to Japan’s wartime history, have since been removed from the platform.
[0] https://www.cnn.com/2025/01/16/tech/tiktok-refugees-rednote-...
Thanks for the ref. Not sure why that particular user got banned. A search just now on RedNote using the hashtag "gay" returns 8.7k posts. The results show plenty of men in skimpy clothing with uncovered nipples.
Not at all. There are hundreds of thousands of US users. Most of the content I see is localized and tailored for English. There’s even an auto translate feature. They’re very welcoming and nice, and encourage us to post. Most of them are just showing their houses and what it’s like to live in China.
It was a pleasant surprise. That said, I’m not too interested in endless house tours, so I’m going to see what kind of content there is when things settle down. That’s still a migration though, at least for me.
What is impressive to me as a software developer is that the RedNote engineering team added a Translate item to the system, at scale, within a matter of days. It works flawlessly.
I was on RedNote just now. I saw some gay content that had been there yesterday as well, and has not been removed.
BTW, the RedNote userbase in China is 70% female, similar to Pinterest in the US. That may be why there's an affinity with a portion of the Tiktok userbase. The RedNote users are not into politics (at least were not). They cats, cooking, fashion, interior decorating, travel, sports.
rayval commented on Canvas is a new way to write and code with ChatGPT openai.com/index/introduc... · Posted by u/davidbarker
Won't need most of humanity wasting time gatekeeping and toiling, to instead focus on study and leisure.
That would be nice, to gambol in a lush, sunny meadow, perusing a leather-bound volume that we read in the original Greek or Sanskrit.
Unfortunately, I fear we will instead end up sweaty and dirty and bloodied, grappling in the parched terrain, trying to bash members of a neighboring clan with rocks and wooden clubs, while a skyline of crumbling skyscrapers looms in the distance.
Dead Comment
rayval commented on Doomretro – The classic, refined DOOM source port. For Windows PC github.com/bradharding/do... · Posted by u/keepamovin
The wiki says Doomretro is 180,000 lines of code. That seems high to me, without ever having looked at the code.
I have worked on simple games in the past which are in the low tens of thousands LOC. I understand AAA games can be several millions of lines of code. Minecraft is reportedly 1.8M.
However, Chocolate Doom (the precursor for Doomretro) is around 50kloc, according to [1]. Wonder what changes were made to more than double the code size.
[1] https://medium.com/@atroche/a-quick-comparison-of-the-size-o...