Business Process Automation

OpenAI has unveiled a groundbreaking advancement in AI safety with the research preview release of its gpt-oss-safeguard models, introducing two open-weight safety reasoning systems – 120b and 20b – that enable developers to enforce custom safety policies dynamically during inference time. Unlike traditional moderation models constrained by fixed policies requiring retraining for updates, these models leverage policy-conditioned safety mechanisms, allowing real-time adaptation to evolving guidelines without altering their core architecture. Open-weight models, which permit parameter adjustments without full retraining, represent a paradigm shift in AI governance, particularly for addressing domain-specific risks like fraud, self-harm, or game abuse. Licensed under Apache 2.0 and accessible via Hugging Face for local deployment, the models underscore OpenAI’s commitment to transparency and flexibility. By decoupling...

In Franklin, Tennessee, a homebuyer stumbled upon a seemingly perfect real estate listing video featuring luxury furniture, a wine cellar, and a smiling agent – all entirely ai generated real estate content while the actual property was empty. Tools like AutoReel enable agents to create such content in minutes, with between 500 and 1,000 new listing videos being generated daily across the US and even in New Zealand and India. This rapid adoption of ai real estate tools raises significant concerns about the erosion of authenticity in high-stakes transactions. As the industry embraces efficiency gains, it risks undermining trust, ushering in what some are calling the ‘AI slop era’ where digital fabrication threatens to mislead consumers. The AI Revolution: How...

OpenAI announced on Thursday it has acquired Software Applications, Inc., the makers of an AI-powered natural language interface for Mac computers called Sky [1]. Sky, which had not been released to the public, aims to revolutionize productivity by acting as an agentic AI assistant across apps. Unlike other AI interfaces, Sky can observe screens and take action within applications, seamlessly integrating with Mac workflows. This acquisition marks a pivotal step for OpenAI to embed its technology into daily computing experiences, leveraging Large Language Models (LLMs) like GPT to enhance user interaction. In contrast, Apple, known for its cautious approach to AI, is set to launch an overhauled Siri with AI capabilities next year, alongside other Apple Intelligence Features [2]. Sky’s...

Amazon has unveiled a prototype of AI-powered smart glasses named ‘Amelia’ for delivery drivers, marking a significant step in enhancing logistics efficiency. These smart glasses, which include a camera and display, are designed specifically for the ‘last mile’ of delivery networks, integrating seamlessly with a waistcoat button that allows drivers to take photos of deliveries. Amazon is testing the Amelia glasses with over a dozen delivery service partners and hundreds of drivers across the country, emphasizing their focus on improving operational efficiency. Amazon is the latest US tech giant to enter an increasingly crowded field of firms experimenting with wearables [2]. Smart glasses, like Amelia, are wearable devices with built-in displays and sensors that provide users with digital information in...

What happens when your first ten hires aren’t people at all? This isn’t a hypothetical question pulled from a science fiction novel; it’s a strategic query being posed in boardrooms and pitch meetings across Silicon Valley, and it’s set to be the defining debate at this year’s most anticipated tech gathering. The traditional startup playbook – built on human hustle, late-night coding sessions, and a relentless drive to build a core team – is being fundamentally challenged. A new, radical approach to company building is emerging from the crucible of generative AI, one that prioritizes autonomous code over human capital in the critical early stages of growth. This paradigm shift suggests that the most efficient path to scale might not...

Google has rolled out its latest preview models, Gemini 2.5 Flash and Flash-Lite, across AI Studio and Vertex AI, fundamentally shifting the conversation towards speed and efficiency. The headline news comes from external benchmarks, which report that Gemini 2.5 Flash-Lite is now the fastest proprietary model available, clocking in at approximately 887 output tokens per second. This performance leap is paired with a significant reduction in output tokens, promising lower latency and direct cost savings for developers. Alongside these updates, Google introduced a crucial deployment choice for teams managing their AI models [1], a concept known as rolling aliases vs. pinning. This refers to two strategies: ‘pinning’ a specific, unchanging model version for production stability, or using a ‘rolling alias’...

OpenAI is fundamentally shifting the landscape of AI evaluation with its new GDPval suite, designed to measure model performance on real-world, economically valuable tasks [1]. Moving beyond abstract academic benchmarks, this framework assesses AI capabilities across 44 occupations within nine major U.S. economic sectors. At the heart of GDPval is a methodology grounded in practical utility: blinded pairwise comparisons. In this evaluation method, a human expert reviews two outputs side-by-side without knowing their source – for instance, which was created by an AI – and simply chooses the better one, providing a direct and unbiased judgment of quality. This approach replaces abstract scores with direct, qualitative judgments on authentic deliverables. To facilitate broader research, OpenAI has also released a 220-task...

The vision has been a staple of tech keynotes for years: truly autonomous silicon valley ai agents – software programs designed to perceive their environment and take actions to achieve goals, like booking travel or managing expenses on a user’s behalf – seamlessly operating our digital lives. Yet, the current reality falls short. Anyone who has experimented with today’s consumer-facing agents, from OpenAI’s ChatGPT Agent to Perplexity’s Comet, knows they remain brittle and limited, a fact that tempers excitement around assets like OpenAI stock. To bridge this gap between promise and performance, a new set of techniques is required. A critical element is now emerging from the research labs into the startup ecosystem: reinforcement learning environments. Much like how vast,...

In a significant move that could reshape the landscape of speech AI, Xiaomi’s MiMo team has officially unveiled MiMo-Audio, a model whose scale and architectural philosophy signal a new era for audio-language processing. The new release is Xiaomi’s MiMo-Audio, a 7B Speech Language Model trained on over 100 million hours of audio 1, a colossal effort that pushes the boundaries of data and parameter counts. Yet, beyond the staggering numbers lies a fundamental paradigm shift. MiMo-Audio abandons the complex, multi-component systems that have long dominated the field, instead operating on a single, elegant principle: a unified model that processes interleaved streams of text and discretized audio without specialized, task-specific heads. At the heart of this innovation is a unified Next-token...