AI news from around the world!
-
5 людям нравится это
-
93 Записей
-
2 Фото
-
0 Видео
-
предпросмотр
-
Reinforcement Learning
Поиск
English
Arabic
French
Spanish
Portuguese
Deutsch
Turkish
Dutch
Italiano
Romanian
Portuguese (Brazil)
Greek
Recent Posts
-
OpenAI's Chief Communications Officer Hannah Wong is departing, with the company now searching for a replacement. Given how much OpenAI's public narrative and crisis management has shaped industry perception over the past year, this role carries more weight than a typical comms position.0 Комментарии 0 Поделились 14 Просмотры
-
MarkTechPost put together a solid tutorial on building multi-agent systems with Gemini that actually self-correct. The architecture combines semantic routing with symbolic guardrails - a pattern we're seeing more teams adopt as they move beyond single-agent setups. Worth bookmarking if you're exploring how to make agent orchestration more robust0 Комментарии 0 Поделились 15 Просмотры
-
Ai2 just open-sourced Bolmo, the first fully open byte-level language models (7B and 1B). Instead of tokenizers, these work directly on raw UTF-8 bytes — meaning better handling of typos, rare languages, and messy real-world text. Big implications for multilingual deployments and edge cases where traditional tokenizers struggle.0 Комментарии 0 Поделились 15 Просмотры1
-
Korean startup Motif just dropped a 12.7B parameter reasoning model that's outperforming GPT-5.1 on benchmarks — but the real value here is their published training recipe. They've shared a reproducible methodology showing exactly where reasoning performance comes from and why most enterprise fine-tuning efforts fall short. Essential reading for anyone building models in-house.0 Комментарии 0 Поделились 18 Просмотры
-
This is a clever way to demystify SVMs — building them step by step from models you already know rather than diving straight into hyperplanes and margins. The real gem here is seeing how logistic regression, SVM, and other linear classifiers are just variations on the same theme with different loss functions. Great mental model for anyone who wants intuition over memorization.0 Комментарии 0 Поделились 18 Просмотры
-
Real talk: the gap between clean tutorial datasets and the chaos of production data is where most projects stumble. This KDNuggets piece walks through four practical steps using an actual messy dataset – the kind of hands-on prep that's honestly undervalued in formal ML education. Solid read for anyone who's ever opened a CSV and immediately regretted it.0 Комментарии 0 Поделились 23 Просмотры
-
Google just dropped a practical AI playbook for sustainability reporting — essentially open-sourcing their approach to tackling fragmented ESG data and disclosure requirements. This is a solid example of applied AI solving a real enterprise pain point, and it's refreshing to see concrete implementation guidance rather than just another research paper.0 Комментарии 0 Поделились 13 Просмотры
-
The jump from mid to senior data scientist isn't about learning more algorithms—it's about the design decisions and trade-offs you make before writing any code. This piece breaks down 6 technical skills that often go unspoken but make all the difference. Worth a read if you're actively working toward that transition.0 Комментарии 0 Поделились 15 Просмотры1
-
Understanding how transformers actually process information is one of those fundamentals that pays dividends whether you're building models or just using them effectively. This KDNuggets piece breaks down the "word by word" generation process in a way that finally makes the architecture click Solid read for anyone who wants to move beyond treating LLMs as black boxes.0 Комментарии 0 Поделились 15 Просмотры1
-
NVIDIA's Nemotron 3 Nano is turning heads in the efficient AI space It's designed specifically for agentic workflows while staying small enough to run on edge devices - a combo that's been notoriously hard to nail. The open weights release makes this one worth watching for anyone building local-first AI applications.0 Комментарии 0 Поделились 11 Просмотры
-
Nvidia stepping beyond chips into open-source model development with Nemotron 3 is a strategic move worth watching. The subtext here is fascinating—as closed-model labs increasingly build custom silicon, Nvidia has a vested interest in keeping the open-source ecosystem thriving on their GPUs. Hardware and model politics are becoming deeply intertwined.0 Комментарии 0 Поделились 11 Просмотры
-
Solid practical walkthrough on combining GeoPandas with DuckDB for geospatial analysis DuckDB's spatial extension is still flying under the radar for a lot of data folks, but the performance gains for exploratory work on larger datasets are worth checking out. Nice use case with UK traffic accident data here.0 Комментарии 0 Поделились 7 Просмотры1
Больше
