Algodato

Natural Language Logic and the End of the Manual Formula

As the AI spreadsheet automation market approaches a projected $2.48 billion valuation by 2034, the focus is shifting from simple automation to the high-stakes challenge of numerical accuracy and the psychological transition of trusting an agent with our personal finances.

Moving Pictures: The Practical Reality of 2026 Video Generation Models

As video generation moves from research labs to accessible APIs like OpenRouter, we examine the trade-offs between visual fidelity, cost, and the human cleanup required to produce usable footage in 2026.

Why Prompt Caching is Changing the Economics of Daily AI

As AI models grow more capable, the compute cost to run them becomes the primary friction for widespread use. Prompt caching offers a way to lower these costs by storing recurring queries, fundamentally changing how we interact with intelligent systems.

The Persistence of Error: How AI Fabrications Are Entering the Permanent Record

As AI-generated errors slip past peer reviewers and editors into academic journals and books, the baseline of human knowledge is absorbing fabrications that are becoming nearly impossible to purge.

Scaling the Smart Floor: Why Manufacturing AI is Moving from Pilot Programs to $48 Billion Reality

As the AI manufacturing market targets a $48.6 billion valuation by 2035, the real shift is moving away from rigid automation toward flexible systems that handle the messiness of the physical world.

The AI Efficiency Paradox: Why Faster Automation is Leading to Higher Bills

New data on AI procurement and cloud management reveals that the transition from human labor to automated agents is creating a new category of 'shadow spend' that often exceeds initial budgets.

Unbundling the Search Bar: Analyzing Klarna’s Intent-Based Shopping App for ChatGPT

Klarna’s move to integrate specialized shopping search into ChatGPT marks a shift from keyword-based product grids to intent-driven discovery. We analyze how this impacts task completion and user friction in everyday commerce.

Moving Away From Rigid Frames: How Adaptive Growth Changes Robot Repairability

Traditional consumer robots are static tools that fail when a single motor or gear wears out. New advances in modular, bio-inspired growth are shifting robots toward organic adaptability, allowing systems to self-repair and physically expand their capabilities.

Beyond the Unread Pile: How OpenEnv is Quantifying the Future of Autonomous Email Triage

As AI agents move from writing drafts to managing entire inboxes, new benchmarks like OpenEnv are revealing the messy reality of delegating our digital lives to machines.

Choosing Your AI Interface: A 2026 Guide to Browsing Agents and ChatGPT Atlas

With the 2026 arrival of ChatGPT Atlas, the web browser has moved from a static viewer to an active research agent. We compare task success rates, privacy models, and human-cleanup loads across the market leading tools.

Beyond the Search Bar: How AI is Reshaping Human Task Execution

Recent research from Jakob Nielsen identifies a critical shift in how we interact with technology: AI is expanding the variety of tasks we attempt, while simultaneously narrowing the information we receive. This evolution changes the primary burden from searching to supervising.

The Physical Reality of Home Robots: Managing Noise and Spatial Constraints in 2026

As domestic robots evolve from simple vacuums to mobile manipulators, their ability to function is being constrained less by intelligence and more by the acoustic and spatial realities of everyday living environments.

Clinical Rigor in the Classroom: Inside the 1,525 Student AI Tutoring Trial by Eedi and Google DeepMind

A major UK-based trial is moving AI tutoring from general curiosity to measurable science, testing whether student-level context can solve the reliability issues that plague current educational automation.

Mapping the Ghost Edge: How Users Discover the Limits of AI and Robotics

In 2026, users have moved past novelty toward functional probing. We analyze the data behind how people form mental models of machine reliability and where the boundaries of trust actually lie.

Managing the Latency and Safety Trade-offs of Enterprise AI-DLP Systems

As enterprises move from banning AI to governed adoption, tools like Seclore ARMOR AI-DLP aim to balance data protection with model performance. We analyze the operational impact of integrating real-time security layers into AI workflows.

The Speed Gap: Quantifying Real-World Latency and Throughput in 2026 AI Models

A technical breakdown of current LLM response times, measuring the trade-offs between Time to First Token (TTFT), sustained throughput, and output quality across frontier and edge architectures.

Terminal Velocity: Measuring the Operational Performance of Humanoid Robots in Japanese Aviation

Analyzing the shift from robotics demonstrations to high-stakes deployment at Japanese airports, evaluating cost-per-task, reliability metrics, and the reality of human-in-the-loop intervention in 2026.