Where to Submit your AI tool
Here are some good AI tool directories where you can submit your AI tool: Ailabhub Online – https://www.ailabhub.online/
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Roundtables: Inside the Musk v. Altman Trial
Listen to the session or watch below Elon Musk lost his suit against OpenAI, in which he alleged CEO Sam Altman and President Greg Brockman had deceived him over the company’s non-profit status. Watch as AI reporter and attorney Michelle Kim, who covered the trial for MIT Technology Review, joins in conversation with editor in
The Hidden Margin Tax: Why Generic AP Software Is Quietly Costing Freight Forwarders Millions
Freight forwarding accounts payable is unlike any other AP function. Variable carrier costs, late vendor invoices, multi-currency settlements, customs duties, and shipment-level reconciliation make every invoice a financial puzzle. Manual AP processing absorbs these problems quietly until margins start to erode. PaperEntry AI: AP Invoice Automation from Deep Cognition is purpose-built to solve this. It
Cline Releases Cline SDK: An Open-Source Agent Runtime Now Powering Its CLI and Kanban, With IDE Extensions Being Migrated
Cline became ‘agentic’ before it was cool, but building on the bleeding edge usually leads to some structural debt. Over time, the agent loop and the VS Code extension became a package deal—making it a headache to maintain or move to new environments. Its tough to just keep layering features on a rigid core. Cline,
Reflections from #AIES2025
In this piece, we reflect on AIES 2025, and outline the conversations and presentations from a discussion session on LLMs in the context of clinical usage and human rights. This is a crosspost from the latest issue of AI Matters, published by the ACM SIAGI. This year’s conference on artificial intelligence, ethics and society (AIES)
Forecasting accuracy improves 5.9% at North Carolina Education Lottery
Every lottery ticket printed is a forecast – and when that forecast is wrong, the consequences are immediate. “If the ticket’s there, you buy it. If the display is empty, you walk away,” said Kyle Gray, Insights and Analytics Manager at the North Carolina Education Lottery. “That moment is forecasting.” […] The post Forecasting accuracy
Forecasting accuracy improves 5.9% at North Carolina Education Lottery Read More »
Meta AI Releases Sapiens2: A High-Resolution Human-Centric Vision Model for Pose, Segmentation, Normals, Pointmap, and Albedo
If you’ve ever watched a motion capture system struggle with a person’s fingers, or seen a segmentation model fail to distinguish teeth from gums, you already understand why human-centric computer vision is hard. Humans are not just objects, they come with articulated structure, fine surface details, and enormous variation in pose, clothing, lighting, and ethnicity.
From Tools to Agents: How orchestrated decision intelligence is reshaping S&OP
For decades, supply chain software has been defined by tools — forecasting tools, optimization tools, scenario tools, dashboards, and planning applications. Each is designed to perform a specific task well. But as supply chains become more volatile and tightly coupled, the biggest challenge is no longer analytical sophistication. It’s coordination. […] The post From Tools
From Tools to Agents: How orchestrated decision intelligence is reshaping S&OP Read More »
DeepSeek AI Releases DeepSeek-V4: Compressed Sparse Attention and Heavily Compressed Attention Enable One-Million-Token Contexts
DeepSeek-AI has released a preview version of the DeepSeek-V4 series: two Mixture-of-Experts (MoE) language models built around one core challenge making one-million-token context windows practical and affordable at inference time. The series consists of DeepSeek-V4-Pro, with 1.6T total parameters and 49B activated per token, and DeepSeek-V4-Flash, with 284B total parameters and 13B activated per token.
Google DeepMind Introduces Decoupled DiLoCo: An Asynchronous Training Architecture Achieving 88% Goodput Under High Hardware Failure Rates
Training frontier AI models is, at its core, a coordination problem. Thousands of chips must communicate with each other continuously, synchronizing every gradient update across the network. When one chip fails or even slows down, the entire training run can stall. As models scale toward hundreds of billions of parameters, that fragility becomes increasingly untenable.