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AIHiggsfield has updated its AI influencer tool, letting users insert their own AI-created characters into existing videos. The characters look realistic but deliberately unhuman, with geometric haircuts and elongated necks, as a spokesperson said a flawless face reads as generic AI. The company, which says it has 30 million users, recently announced a $1 billion run rate.
0xMarioNawfal@RoundtableSpaceXAI score23AIAn open-source GitHub repository called AI Engineer Headquarters offers a structured curriculum for aspiring AI engineers. According to the post, it covers fundamentals, large language models, RAG, fine-tuning, tool calling, and agentic workflows.
NVIDIA AI@NVIDIAAIOfficialAI score38AISynthID Detector is now publicly available, letting anyone check whether content is SynthID-watermarked. NVIDIA watermarks content generated by its Cosmos models on build.nvidia.com, so uploaded Cosmos output can be verified as coming from NVIDIA's models.
Google for Developers@googledevsOfficialAI score38AIAntigravity can build and test native Android apps by connecting the Stitch MCP and Android CLI. The agent imports UI designs, converts them into native Jetpack Compose components, validates them in an emulator, and runs the final build on a physical device.
elvis@omarsar0XAI score22AIElvis Saravia reports that agent-to-agent communication with a personal agent, built on models like Opus 5.5, is already coordinating work faster and at higher quality than he can match. He describes progressing from individual Claude Code sessions to subagents, then a persistent team of eight specialized bots with his own orchestrator. He argues everyone should build a personalized agent orchestrator and says most apps like Code and Claude Desktop are behind.
Yuchen Jin@Yuchenj_UWXAI score34AIA startup's founders report that a single engineer built polished, reliable web, desktop, iOS, and Android apps in six months using AI. The post argues AI is turning 10x engineers into 100x engineers, a capability it says was not possible last year.
AIReflection AI and Mistral each unveiled new open-source models this week, aiming to beat other Western open models, though they trail top Chinese and closed systems on prominent benchmarks. Reflection CEO Misha Laskin says the target is regulated industries and governments that cannot or will not use Chinese models. The outcome depends on whether businesses and agencies accept less advanced models for some tasks in exchange for lower cost and more control.
Liquid AI@liquidaiOfficialAI score40AILiquid AI has released its d1 decision models, with d1-3B recommended for high-quality text and vision tasks and d1-omni-600M offered as an experimental option for smaller footprints. The weights are available for download, fine-tuning, and local deployment.
Liquid AI@liquidaiOfficialAI score38AILiquid AI's Open d1 models run across NVIDIA DGX, RTX, and Jetson hardware, with day-one llama.cpp support for deployment anywhere. Measured one request at a time, the d1-3B model's single-question latency is 8 ms on an NVIDIA RTX 4090, 16 ms on Jetson AGX Thor, 26 ms on Jetson AGX Orin 64 GB, and 50 ms on Jetson Orin Nano.
Liquid AI@liquidaiOfficialAI score30AILiquid AI built 10 live-camera demos for its d1-3B model, ranging from gesture-controlled games to content moderation, each using one forward pass per frame. In collaboration with NVIDIA Robotics, the company also showed d1-3B navigating an environment in Isaac Sim, served on a Jetson in a hardware-in-the-loop setup.
Liquid AI@liquidaiOfficialAI score36AILiquid AI has released d1-omni-600M, an experimental 600M-parameter model that handles text plus image or audio input. It combines LFM2.5-Encoder-350M with vision and audio encoders and leads the company's text benchmark comparison on toxicity detection and paraphrase identification. The post suggests uses such as voice-command routing, on-device moderation, and intent classification.
Liquid AI@liquidaiOfficialAI score23AILiquid AI's d1-3B ranks first among models under 10B parameters on the Decision Index v0.2.1, a benchmark for structured decision-making. Built from LFM2.5-VL-3B, it makes decisions from text and images in a single pass. It is suited to reranking, agent guardrails, and visual inspection.
Liquid AI@liquidaiOfficialAI score52AILiquid AI released Open d1, two open-weight multimodal models in its d1 decision model family. The d1-3B model supports text and vision, while d1-omni-600M supports text plus image or text plus audio. The source says the models are meant for real-time decision making across data centers, RTX workstations, and Jetson edge devices.
AILiquid AI released two open-weight decision models, d1-3B and d1-omni-600M (experimental), built on its Liquid Foundation Models and available on Hugging Face. d1-3B scores 48.57 on the Decision Index 0.2.1, the highest among decision models under 10B parameters, and answers a question in 16 ms on an NVIDIA Jetson AGX Thor and under 50 ms on a Jetson Orin Nano. The models support text and images (d1-3B) or text with image or audio (d1-omni-600M).
Mark Chen@markchen90XAI score46AIMark Chen says the Navier-Stokes achievement matters more for the figure it shows than for the problem itself, representing a decade of mathematical progress in a single week. He says he is eager to apply these tools to life sciences, the building of OpenAI's next models, and alignment research.
Google@GoogleOfficialAI score44AIGoogle is launching its first TPUs into orbit to test how hardware holds up under solar events, cosmic rays, and radiation-induced bitflip errors. The post says these conditions can only be tested in space.
Google@GoogleOfficialAI score42AIGoogle launched its first test satellite carrying four TPUs into orbit last week as part of Project Suncatcher, a moonshot exploring whether machine learning infrastructure could one day operate in space. The test aims to determine whether Google's AI hardware can withstand the physical stress of spaceflight and the radiation and thermal extremes of orbit.
Nous Research@NousResearchOfficialAI score38AINous Research has raised a Series B, as reported by the Wall Street Journal, to bring its Hermes Agent to new frontiers and build a mobile app. Investors include Nvidia, M12, Samsung Next, Robot Ventures, USV, Y Combinator, and Menlo Ventures, among others.
Gamma@GammaAppOfficialAI score43AIGamma announces Gamma 5, which it calls its biggest update, rebuilding its engine from the ground up. The release adds an agent for brainstorming, research, and editing, plus style control from described looks or visual inspiration. It also supports importing and exporting PowerPoints, PDFs, and company brand, with connections to Slack, Notion, Salesforce, Claude, and ChatGPT.
Google Cloud Tech@GoogleCloudTechOfficialAI score34AIGoogle DevRel's James O'Reilly explains how Antigravity Agent Plugins expose local MCP server tools to the model, either eagerly as top-level functions or lazily through a call_mcp_tool proxy. Eager loading, set via "eager": true in mcp_config.json, avoids the discovery turn but adds fixed per-turn token overhead that can degrade reasoning with 100+ tools. Lazy loading is the plugin default and keeps baseline token use low, at the cost of an extra proxy hop and a higher chance of JSON quoting errors.
AIPresident Donald Trump is launching a new AI task force as he pursues American AI supremacy, according to Fast Company. The article says he must balance competing factions to keep them satisfied, but the source text provided gives no further details on membership, mandate, or timeline.
AIPresident Donald Trump is launching a new AI task force while balancing competing factions as he pursues American AI supremacy. The source text provided is brief and does not detail the task force's members, mandate, or policies.
AIPresident Donald Trump is launching a new AI task force as he pursues American AI supremacy, according to Fast Company. The article says he must balance competing factions to keep them satisfied, but the source text provided gives no further details on membership, mandate, or timeline.
Tibor Blaho@btibor91XAI score38AIDatabricks announced general availability of on-behalf-of-user (OBO) authorization for Databricks Apps, letting apps act with the signed-in user's identity so Unity Catalog enforces that user's row filters and column masks. Developers can request narrow API scopes such as sql:restricted-query, which allows only read-only SQL queries, while apps keep a dedicated service principal for app-owned operations.
Daniel Han@danielhanchenXAI score48AIUnsloth now lets users train their own decision models locally on just 3GB of VRAM by fine-tuning Qwen, Gemma, and Llama with a Clef head. The post says this raises accuracy from 30% to as high as 78%, and the tool is available through Unsloth Desktop.
LangChain@LangChainOfficialAI score40AILangChain Academy has published a two-minute explainer on agent skills and how they protect an agent's context window. The post promotes its Deep Agents course on the LangChain Academy site.
Aravind Srinivas@AravSrinivasXAI score62AIPerplexity is open-sourcing pplx-embed-v2-late, multi-vector embedding models for text and images in one shared space, in 9B and 0.6B sizes. The 9B model can index multimodal data, the 0.6B model can run queries on device, and PDF pages can be searched without OCR. The author reports 92.4% on MADQA and 64% on BrowseComp+, with weights available on Hugging Face.
Modal@modalOfficialAI score22AITypeSafeAI's Jev reached one trillion tokens served by the Sunday after its Thursday launch, with no signs of slowing, according to Modal. Modal presents the milestone as a case study of how the team scaled Jev on its platform.
Unsloth AI@UnslothAIOfficialAI score40AIUnsloth released an open-source method to fine-tune LLMs into decision models that run locally, lifting Qwen3.5 0.8B's aggregate accuracy from 20.7% to 74.3% across three decision benchmarks. The team used a Clef head with LoRA (r=64) for one epoch on just 4GB VRAM, with the approach applicable to models such as Qwen3.8 and Gemma 4. A guide and notebooks are available on the Unsloth documentation site and GitHub.
AITeradyne Robotics and Elite Robots reached a mutual agreement ending a legal dispute over robots and software, announced Oct. 1 without disclosing settlement terms. The case followed a preliminary injunction issued by the Regional Court of Hamburg against Elite Robots Deutschland over allegedly infringing Universal Robots software, which was not a final finding of infringement. Elite Robots did not admit liability.
Deedy@deedydasXAI score46AIDeedy argues LLMs have made substantial progress on four of the seven Millennium Prize problems, including a claimed Navier-Stokes result, conditional on verification. He says OpenAI's results averaged only 3 hours of thinking compute on unreleased models. He concludes that by most definitions of AGI, we have already achieved it.
Santiago@svpinoXAI score22AIA new model extracts values absent from a document by computing them from figures that are present, such as deriving a yearly product cost from a monthly price. Santiago says the video shows examples of inferring complex formulas. The background post describes this as Higher-Order Extraction, which deterministically computes needed numbers from raw page values.
AIGitHub is rolling out a fine-tuned, purpose-built model for secret detection that reads surrounding code to identify likely credentials, including passwords without recognizable token formats. Existing AI-detected Password alerts have been upgraded automatically, and AI-detected secrets in push protection is in private preview. New opt-in checks in push protection and the GitHub Copilot /security-review command will consume GitHub AI Credits.
Perplexity@perplexity_aiOfficialAI score27AIPerplexity has published both pplx-embed-v2 models on Hugging Face, with the collection available at the linked URL. The post provides no further details on model sizes, benchmarks, or capabilities.
Perplexity@perplexity_aiOfficialAI score32AIPerplexity reports its system reached 92.4% accuracy on MADQA, a benchmark of 500 questions over 800 PDFs. The post describes this as the top result among retrievers on that benchmark.
Perplexity@perplexity_aiOfficialAI score34AIIn agentic search, a GPT-OSS-120B agent using the 9B model answers 64.0% of BrowseComp+ questions correctly, 4.9 points ahead of the next ColBERT model. It also uses fewer searches than any baseline.
Perplexity@perplexity_aiOfficialAI score22AIOn the Q2D-Web benchmark of about 70,000 production-derived search queries over 190M web documents, Perplexity's 9B and 0.6B models reach 74.8% and 73.6% Recall@1000. Both outperform nemotron-embed-8b, which scores 69.3%.
Andrew Curran@AndrewCurran_XAI score42AIAndrew Curran notes OpenAI's 722 published mathematical results show striking under-representation of cryptographic breakthroughs, and he says he has personally witnessed US government censorship of academic quantum cryptanalysis results. He calls backroom government interventionism his base case and says rumors suggest yesterday's OpenAI math release was only the first of three batches.
Perplexity@perplexity_aiOfficialAI score41AIPerplexity's 0.6B and 9B models are both distilled token by token from one 18B teacher, so they share a single embedding space. A corpus indexed with the 9B model can be searched using 0.6B queries, raising ViDoRe v3 from 62.3% to 63.5% with no added query cost.
