NodeShift

Did you know that DeepSeek-R1 is shaking up AI? 🫨 This open-source model rivals OpenAI’s o1, offering 671B parameters with only 37B activated per pass, making it powerful and efficient. With reinforcement learning, chain-of-thought reasoning, and self-verification, it excels in math, coding, and logic. We tested three ways to run it locally: Ollama for easy setup, vLLM for speed, and Transformers for full control. Want hassle-free AI deployment? Run it effortlessly on NodeShift.

Hub71 startups are taking part in Machines Can Think to showcase their solutions, resilience, and AI-powered innovations to the wider ecosystem.​ This platform brings founders and industry leaders together to explore how AI is built, scaled, and deployed under real-world business and regulatory challenges.​ Join us to connect and meet the startups driving Abu Dhabi’s future of tech innovation. 🚀 Register now: go.hub71.com/machines-can-t… @Machinescansee | @mbzuai | @1nvoiceMate | @nodeshiftai | @Simpleem_AEI #Hub71 #Startups #Innovation #AI #MCT #InAbuDhabi

- If you work in BFSI, compliance, or AI transformation, this is a must-read 🔗Read the full article: nodeshift.cloud/blog/how-banks…

with zero data leaving the premises. In our latest article, we break down: - How banks can safely use on-prem LLMs for credit memos, risk reviews & KYC - Why public AI tools pose compliance risks - How platforms like NodeShift AI make enterprise-grade private AI possible

Banks process more documents than almost any other industry - credit memos, risk assessments, KYC files, compliance reports, audit responses, and the list goes on. Yet most of this is still manual. - Data copied between systems - Reports reviewed line by line

🔷 How NodeShift AI provides a fully private, production-ready GenAI environment If your org is exploring private AI, this guide is a solid entrypoint. 🔗 Read here: nodeshift.cloud/blog/how-to-de…

In our latest article, we break down: 🔷 What most companies get wrong when trying to deploy on-prem GenAI 🔷 Architecture patterns that actually work 🔷 How to stay compliant with country-level data residency laws

Most organisations want to adopt GenAI, but can’t use it. Why? Because public AI tools transfer your data across borders, often into multiple regions you can’t control. For teams handling confidential, regulated or government data, that’s a hard NO. 🧵⬇️

- Support for 140+ enterprise-grade AI models (ChatGPT, Claude, Gemini, Mistral, LLaMA, DeepSeek & more) If you’re in HR or People Ops, this is a must-read. 🔗 Read the full article here: nodeshift.cloud/blog/how-hr-te…

In our latest article, we break down how a platform like NodeShift AI help HR teams securely automate daily workflows with: - Faster policy drafting - Accurate job description generation - Instant memo + meeting summary creation - Zero data leaving the organisation

Every week, HR is forced to spend hours rewriting the same things: → New policies → Updated job descriptions → Internal memos → Meeting notes → Small announcements that somehow take too long But HR can’t use public AI tools like everyone else. Why?

Abu Dhabi is accelerating sovereign AI adoption with K2 Think, the UAE’s open-source reasoning model engineered by MBZUAI and G42.

At Hub71, the K2 engineering team met with AI-driven startups for a deep dive into how the model is built, and how it can be fine-tuned, integrated, and commercialized across real products and industries.

By connecting research excellence with startup execution, this collaboration advances Abu Dhabi’s leadership in applied and sovereign AI, while reducing reliance on foreign LLMs and enabling innovation that’s built and scaled in the UAE. 🚀🇦🇪 @mbzuai | @G42ai | @cambioml | @nodeshiftai | @HarmonicDiscov | @evoost_ai | @orbii

In our latest article, we break down how to install and run ERNIE 4.5 VL, Thinking, and how NodeShift Cloud makes deploying this next-gen model effortless for developers building visual-language agents and AI reasoning systems. 🔗Read the full guide here: nodeshift.cloud/blog/how-to-in…

Built on Baidu’s powerful 28B-parameter architecture, it brings deep multimodal reasoning, fine-grained grounding, and tool-assisted visual understanding to life - all while running efficiently with just 3B active parameters.

What if an AI could not only see an image but also think about it, like reasoning through data charts, solving STEM problems from photos, and finding interesting insights just by looking at your pictures? That’s exactly what ERNIE-4.5-VL Thinking does.