How to Fine-Tune LFM2 Using QLoRA and DPO: A Complete Step-by-Step Coding Tutorial on Google Colab

In this tutorial, we fine-tune Liquid AI’s LFM2 model through a complete open-source workflow. We start by loading the base LFM2 checkpoint with QLoRA, preparing a chat-style supervised fine-tuning dataset, training a lightweight LoRA adapter using TRL and PEFT, and then merging the adapter back into the model. We also extend the workflow with DPO […]

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Alibaba’s Qwen3.7-Plus supports text, video and imagery inputs at low cost of $0.4/$1.6 per 1M token — but it’s proprietary

Alibaba this week released Qwen3.7-Plus, the latest AI large language model (LLM) in its globally beloved and increasingly expansive Qwen family, boasting more multimodal capabilities and a 60% lower cost than the prior, text-only Qwen3.7-Max model released just weeks ago. However, like its immediate predecessor Qwen3.7-Plus is available only under a “closed” commercial license via

Alibaba’s Qwen3.7-Plus supports text, video and imagery inputs at low cost of $0.4/$1.6 per 1M token — but it’s proprietary Read More »

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Perplexity AI unveils hybrid local-cloud inference system at Computex 2026

Perplexity AI, the fast-growing search startup now valued at $20 billion, unveiled what it calls the first hybrid local-server inference orchestrator at Computex 2026 on Monday night, demonstrating software that autonomously decides — in real time and mid-task — which AI workloads stay on a user’s device and which get routed to frontier models in

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The Agentic Reckoning: Enterprise AI organizations have a runtime problem, not a model problem — and most are building the wrong solution

In Q1 2026, VentureBeat’s Pulse Research surfaced the “Governance Mirage”: the gap between the governance org charts enterprises had drawn and the control layers they had actually built. Forty-three percent said a central team owned AI governance; 23% couldn’t agree on who owned it at all; and 31% named vendor opacity as the single biggest

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Enterprise AI agents keep creating data silos. Microsoft’s Build answer is Microsoft IQ and Rayfin.

Every new AI agent your team deploys starts from scratch: no memory of how the business works, where data lives, or what rules apply. And as agentic coding tools spin up applications faster than anyone can govern them, each one risks becoming another silo outside your data layer entirely. Microsoft is addressing both problems directly

Enterprise AI agents keep creating data silos. Microsoft’s Build answer is Microsoft IQ and Rayfin. Read More »

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Microsoft debuts Surface RTX Spark Dev Box to run large AI models without cloud costs

Microsoft on Monday unveiled the Surface RTX Spark Dev Box, a compact desktop computer designed to let software developers run large AI models on their desks instead of paying for cloud computing — a move that directly challenges the per-token pricing model that has defined the AI industry’s economics since ChatGPT launched three and a

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Microsoft launches MXC, an OS-level sandbox for AI agents, with OpenAI and Nvidia already on board

For the past two years, the technology industry has raced to make AI agents more capable — teaching them to write code, navigate software interfaces, manage files, and orchestrate multi-step workflows with increasing autonomy. What the industry has not done, at least not with any consistency, is answer the question that keeps chief information security

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MiniMax-M3 debuts, eclipsing GPT-5.5 and Gemini 3.1 Pro on key benchmark performance for just 5-10% of the cost

Big news in enterprise AI broke over the weekend as Chinese AI startup MiniMax released its highly anticipated M3 large language model on Sunday evening Eastern time, pairing frontier-tier coding and agentic performance with a 1-million-token context window and native multimodality for a fraction of the cost of leading proprietary models, with pricing starting at

MiniMax-M3 debuts, eclipsing GPT-5.5 and Gemini 3.1 Pro on key benchmark performance for just 5-10% of the cost Read More »

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Anthropic’s browser agent got hijacked 31.5% of the time before safeguards engaged

Across the frontier labs, the highest prompt injection figures published this spring are Anthropic’s. Point a red-teamer at its newest model in a browser, and the attacker hijacked it 31.5% of the time before safeguards engaged. OpenAI, Google, and Meta never gave security leaders a comparable number to set beside it. That figure looks like

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