Math Behind "AI Will Replace Engineers" Is Embarrassingly Wrong
이 영상은 'AI가 엔지니어를 대체할 것이다'라는 주장에 대한 수학적 근거가 잘못되었음을 상세히 설명한다. 신경망과 트랜스포머의 작동 원리, AI 성장의 한계, 하드웨어 및 인프라 병목 현상, 에너지 및 비용 문제 등을 다루며 AI가 일자리를 완전히 대체하기 어려운 현실적인 이유를 분석한다. 또한 AI 도입의 실제 속도와 책임 문제, 신뢰성 한계 등도 함께 논의하여 AI 영향에 대한 현실적인 타임라인을 제시한다.

https://www.youtube.com/watch?v=ItSLny8on5I

#ai #engineering #transformer #hardware #scaling

The Math Behind “AI Will Replace Engineers” Is Embarrassingly Wrong​​​​​​​​​​​​​​​​

YouTube

The guide to RL environments: building and scaling them in the LLM era
해당 뉴스는 강화학습(RL) 환경 구축 및 확장에 관한 가이드로, 특히 대형 언어 모델(LLM) 시대에 맞춘 RL 환경 개발 방법을 다루고 있습니다. 구체적인 내용은 부족하지만, RL과 LLM의 결합에 관심 있는 개발자에게 유용할 수 있습니다. 다만, 기술적 세부사항이나 새로운 신기술 발표는 포함되어 있지 않아 중요도는 중간 수준으로 평가됩니다.

https://huggingface.co/spaces/AdithyaSK/rl-environments-guide

#reinforcementlearning #llm #environment #scaling #guide

The ultimate guide to RL environments: building and scaling them in the LLM era - a Hugging Face Space by AdithyaSK

Building and scaling RL environments for LLM training

Scaling should not mean rising payroll 💷

Many MSPs grow revenue, but costs grow just as fast.

📉 Higher payroll costs
⏳ Slower profitability
📊 Margin pressure

Offshore engineers help MSPs scale without increasing payroll significantly 🌍

✅ More capacity without heavy costs
✅ Better margin control
✅ Efficient growth

A smarter way to grow and stay profitable.

#CostSaving #MSP #Scaling #Automation #Tech

Scale Out With Elastic Clusters

This article describes how to scale out an Azure Database for PostgreSQL flexible server elastic cluster.

LFM2-24B-A2B: Scaling Up the LFM2 Architecture | Liquid AI

Today, we release an early checkpoint of LFM2-24B-A2B, our largest LFM2 model. This sparse Mixture of Experts (MoE) model has 24 billion total parameters with 2 billion active per token, showing that the LFM2 architecture scales effectively to larger sizes.

Delivery models are evolving ⚙️

Rigid team structures struggle to keep up with changing demand.

📊 Workloads shift
🔗 Client needs evolve
⚠️ Static teams limit responsiveness

This impacts MSPs managing growth and delivery performance.

≠ Rigid teams enable scaling
→ Flexible models improve responsiveness and scalability 📈

𝐇𝐀𝐋𝐄𝐗𝐎 𝐏𝐎𝐕:
Flexibility drives sustainable growth

▸ Swipe

#DeliveryModel #MSP #Scaling #ITServices

Master of the Roll-up, of PE and Turnarounds!

Adam Coffey has done it, repeatedly.

60 acquisitions across 9 PE sponsors.

For a deeper look:
👉 https://zurl.co/ZiiWN

This is disciplined scaling.

#AdamCoffey #PrivateEquity #Scaling #BusinessGrowth #WDanielCoxIII

Hiring the wrong engineer is expensive 💷

It costs time, slows delivery, and impacts your team.

📉 Productivity drops
⏳ Delays increase
📊 Momentum slows

MSPs are reducing risk by using pre vetted offshore talent 🌍

✅ Proven engineers
✅ Faster onboarding
✅ Lower hiring risk

A smarter way to hire without the guesswork.

#HiringRisk #MSP #TechHiring #ITOps #Scaling

MSPs are rethinking how they build teams 📊

Traditional hiring is slow and rigid, making it harder to scale.

📉 Growth slows down
⏳ Hiring takes too long
📊 Teams lack flexibility

Flexible staffing is becoming the new standard 🌍

✅ Scale when needed
✅ Reduce hiring risk
✅ Stay agile

A smarter way to grow without being locked in.

#FlexibleWork #MSP #Scaling #TechTeams #Hiring

GitHub update: Some explanation of the failures at an essential piece of software development infrastructure. They're under 90% uptime for the month according to the unofficial status page.
https://github.blog/news-insights/company-news/an-update-on-github-availability/
#development #reliability #scaling #github
An update on GitHub availability

Here’s what we’ve done—and what we’re still doing—to improve our availability and reliability.

The GitHub Blog