Shopify has just announced that its mobile app has moved from React Native (RN) to native development. In 2020, Shopify engineers chose React Native for their main apps, aiming to write code once and run it everywhere. At that time, RN attracted a lot of attention from the mobile‑app community, but performance was a trade‑off. RN can speed up development, yet it requires significantly more effort to optimize.
Now they are switching back to native for a fairly straightforward reason: large language models have made cross‑platform coding almost obsolete. With the same design, AI can generate code for both platforms simultaneously, solving both performance and multi‑platform challenges.
DeepSeek has just released Flash 4.1, which is smarter and faster than the previous Flash V4.
Some users say the performance of 4.1 falls between Flash and Pro v4. It can reach over 400 tokens per second, while the earlier version was only around 100 tokens per second. This version also adds image‑understanding capabilities. The model is already accessible via API at the same price.
I've been using OpenAI for a long time, so I haven't tried DeepSeek yet 😅. I'll give it a look in a few days.
Mới nhìn thấy trang statichost.eu cho triển khai các dự án static website các bạn ạ. Cũng có chức năng kết nối với git và cung cấp môi trường xây dựng mã (build). Đặc biệt sắp tới tích hợp thêm cả CDN nên khả năng trang web tải nhanh hơn từ mọi nơi trên thế giới.
À chỉ static website thôi nhé, chưa thấy có serverless để chạy API server đâu 😅
I often mention Ollama and have even used it before to experiment with small models. Recently, an article titled Friends Don't Let Friends Use Ollama explained why we should stop using Ollama. I was surprised to learn there are so many reasons. Besides their somewhat aggressive emphasis on adding the llama.cpp source—essentially the main driver for running large language models—they also raise a concerning issue about the lack of transparency in their cloud service.
There's also a recent memory‑overflow vulnerability exploit that's quite dangerous 🫣
If you’ve been using rust-analyzer in VSCode as the LSP for Rust, someone recently created Rust Glancer to do the same thing but with up to 100 times less RAM usage 😱
The tool is now on the Marketplace as Rust Glancer, so feel free to give it a try ☺️
Everyone is buzzing about the news that GPT‑6 Astra has officially been launched by OpenAI.
Astra scored 99,9% on ARC-AGI-3 and 100% on ExploitBench, 98% on FrontierMath Tier 4, and has helped solve many long-standing problems in mathematics. In short, Astra has surpassed the basic human action effectiveness level at 96%, and overall is no different from an ordinary person. Sounds familiar, right, that's right, this is the legendary AGI (Artificial General Intelligence), everyone.
Many people believe that Astra's 99.9% score was actually achieved thanks to OpenAI using its own specially optimized framework (responses API harness). When run with the test organizers' neutral framework, Astra only scores around 62% - 62.7%. Astra's Intelligence Index on Artificial Analysis is only 61 points, ranking alongside Grok 4.6 or GPT-5.6 Sol and even behind Opus 5 . In general, scores only reflect part of the picture and shouldn't be trusted absolutely based on advertising like that.
Once again the information above may make some people feel pressured and that it's pointless to have to constantly learn new frameworks or tools, because they risk becoming obsolete after just a few months. Many programmers are deeply concerned about their career prospects amid the rapid-fire release of new models that are becoming increasingly refined. Not to mention if they fall into the hands of "bad actors" then what will happen to humanity 😩
Huh, I looked away and back and thought only Codex was down. Turns out they all went down together, Claude, xAI are gone too, guys.
Gemini is still alive and kicking, and the providers in China don't seem to be affected either. I wonder why they all went down together? Probably AWS or Cloudflare 🥶
NVIDIA to acquires Hugging Face.
One side is a chip manufacturer, the other is a platform hosting millions of AI models. Wow, what products are we going to get next 😱
I haven't seen anyone mention it at all, so I forgot too. A few weeks ago Meta launched the Agents Code tool Muse Code, along with the Muse Spark model families made specifically for it. I tried Muse Spark 1.2 but wasn't all that impressed, probably because I haven't had it tackle my everyday work yet so I haven't seen much value.
Last weekend Muse Code shed its experimental (beta) label to move into a stable release, today Meta followed up by releasing Muse Spark 1.3 with extremely impressive scores, far surpassing its previous 1.2 predecessor.
Well I guess I'll have to give it a try and see 😁. Muse Code is selling monthly renewal plans now, starting at just 5$ and apparently you get 10-50 requests every 5h
Early in the morning I read the news that Anthropic released Claude Fable 5.1 and Claude Mythos 5.1, adding to their 2 most premium models then in the evening I read more news that Google released Introducing Gemini 3.8 Flash and 3.8 Flash Cyber - 2 more models in the Flash line - meaning a balance between performance and price.
It seems like Google is continuously releasing models that ease the financial burden on users instead of focusing on the premium segment like the Pro lines as they did before or what 🤔? Or maybe they're also keeping something absolutely massive under wraps so that later they can suddenly go... surprised? 😅
À quên không nói mặc dù là Flash nhưng điểm hiệu năng không hề kém cạnh với cái tên Opus đâu đấy nhé 😎