Vikash P

Vikash Pal is an AI/ML Engineer at ScholarEase and Editor for AIML Insights, focusing on machine learning, applied AI workflows, and practical implementation.

50 Best AI Tools in 2025

50 Best AI Tools in 2025: AI tools command center showing writing, research, coding, design, SEO, video, automation, business productivity, and analytics workflows

The 50 Best AI Tools in 2025: A Practical List by Use Case The 50 best AI tools in 2025 help with writing, research, coding, design, video, meetings, automation, business, education, and productivity. The smartest choice is not the longest tool list. It is choosing a small stack that solves your actual workflow problems without […]

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OpenAI o3 Rare Disease Study: What the 18 Diagnoses Really Show

OpenAI o3 rare disease study workflow with genomic analysis expert review and laboratory confirmation

OpenAI o3 Helped Experts Revisit 376 Unsolved Rare-Disease Cases A study published in NEJM AI on June 18, 2026 used OpenAI o3 Deep Research to reanalyze 376 rare-disease cases that had remained unsolved after earlier specialist review. The result was not autonomous diagnosis. The model generated evidence-linked hypotheses that physicians and genetic experts investigated through

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MosaicLeaks AI Agents: How Web Searches Can Expose Private Files

: MosaicLeaks AI agents exposing private document information through public web searches

AI Research Agents Can Leak Private Files Without Uploading Them Researchers published MosaicLeaks on May 29, 2026, revealing a privacy weakness in AI research agents that combine confidential documents with public web search. The risk is subtle. An agent does not need to upload an internal report or paste a secret into one search box.

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Proactive Coding Agent Benchmark: Google’s Jules Research Explained

Proactive coding agent benchmark measuring useful code insights before developers ask

Google Wants Coding Agents to Spot Problems Before Developers Ask Google published a preliminary evaluation framework for proactive coding agents on June 22, 2026, arguing that current benchmarks do not measure whether an AI system can notice useful engineering problems before a developer explicitly assigns them. The research matters because coding agents are already becoming

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FAPO Prompt Optimization: Cisco’s LLM Pipeline System Explained

FAPO prompt optimization diagnosing and improving a multi-step LLM pipeline

Cisco’s FAPO Can Fix the Weakest Step in an AI Pipeline Cisco Foundation AI published FAPO on June 17, 2026, introducing an automated system for optimizing multi-step LLM applications rather than tuning one prompt in isolation. The research matters because modern AI systems rarely make only one model call. A production pipeline may retrieve documents,

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The 50 Best AI Tools in 2025

The 50 Best AI Tools in 2025:AI tools command center showing writing, research, coding, design, SEO, video, automation, business productivity, and analytics workflows

The 50 Best AI Tools in 2025: Complete Guide by Use Case The 50 best AI tools in 2025 are not useful because they are trendy. They are useful because they solve specific work problems: writing, research, coding, design, automation, video, meetings, business, education, and productivity. The best approach is to choose tools by workflow,

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prime-rl 0.6.0 Scales Agentic RL to Trillion-Parameter Models

prime-rl 0.6.0 training trillion-parameter AI agents across distributed GPU infrastructure

Prime Intellect Can Now Train Trillion-Parameter AI Agents on Real Coding Work Prime Intellect released prime-rl 0.6.0 on June 21, 2026, expanding its open-source reinforcement-learning framework to support trillion-parameter mixture-of-experts models on demanding agentic workloads. The release matters because training an AI coding agent is much harder than training a model to answer one short

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