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News FAUN.dev() Team Trending

@kala shared an update, 2 weeks, 5 days ago

FAUN.dev()

DeepSeekMath-V2 Launches with 685B Parameters - Dominates Math Contests

#DeepSee... #AI mode... #Machine... #Mathema...

DeepSeekMath-V2, an AI model with 685 billion parameters, excels in mathematical reasoning and achieves top scores in major competitions, now available open source for research and commercial use.

DeepSeekMath-V2 Launches with 685B Parameters - Dominates Math Contests

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@anjali shared a link, 2 weeks, 5 days ago

Customer Marketing Manager, Last9

9 Monitoring Tools That Deliver AI-Native Anomaly Detection

A technical guide comparing nine observability platforms built to detect anomalies and support modern AI-driven workflows.

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@kala added a new tool DeepSeekMath-V2 , 2 weeks, 5 days ago.

News FAUN.dev() Team Trending

@kala shared an update, 2 weeks, 5 days ago

FAUN.dev()

A New Challenger: INTELLECT-3's 100B Parameters Punch Above Their Weight

#LLMs #INTELLE... #Mixture... #PRIME-R... #Reinfor...

INTELLECT-3, a 100B+ parameter model, sets new benchmarks in AI, with open-sourced training components to foster research in reinforcement learning.

A New Challenger: INTELLECT-3's 100B Parameters Punch Above Their Weight

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@kala added a new tool INTELLECT-3 , 2 weeks, 5 days ago.

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@devopslinks added a new tool Lustre , 2 weeks, 5 days ago.

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@varbear added a new tool Slurm , 2 weeks, 5 days ago.

Course

@eon01 published a course, 2 weeks, 6 days ago

Founder, FAUN.dev

Cloud Native CI/CD with GitLab

#Cloud N... #DevOps #GitLab ... #docker #kuberne...

From Commit to Production Ready

Course

@eon01 published a course, 3 weeks, 1 day ago

Founder, FAUN.dev

Observability with Prometheus and Grafana

#Grafana #metrics #monitor... #observa... #prometh...

A Complete Hands-On Guide to Operational Clarity in Cloud-Native Systems

Observability with Prometheus and Grafana

Course

@eon01 published a course, 3 weeks, 1 day ago

Founder, FAUN.dev

Cloud-Native Microservices With Kubernetes - 2nd Edition

#Cloud N... #Istio #docker #kuberne... #prometh...

A Comprehensive Guide to Building, Scaling, Deploying, Observing, and Managing Highly-Available Microservices in Kubernetes

Cloud-Native Microservices With Kubernetes - 2nd Edition

Gemini 3 is Google’s third-generation large language model family, designed to power advanced reasoning, multimodal understanding, and long-running agent workflows across consumer and enterprise products. It represents a major step forward in factual reliability, long-context comprehension, and tool-driven autonomy.

At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.

Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.

Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.

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