AI News Archive: August 4, 2026 — Part 12
Sourced from 500+ daily AI sources, scored by relevance.
- AMD’s AI engine shifts into higher gear as data center revenue more than doubles, Helios ramps & market is confused
Advanced Micro Devices Inc. delivered another strong quarter Tuesday, beating Wall Street expectations as its artificial intelligence infrastructure business continued its rapid expansion. The company posted 107% year-over-year growth in data center revenue, reinforcing that AMD is becoming a formidable challenger in the race to power enterprise AI. The Santa Clara, California-based chipmaker reported second-quarter […] The post AMD’s AI engine shifts into higher gear as data center revenue more than doubles, Helios ramps & market is confused appeared first on SiliconANGLE .
- Red Hat leads open-source project to automate AI governance
IBM Corp.’s Red Hat subsidiary today announced the formation of asago, an open-source community project intended to turn artificial intelligence governance policies into operational controls that can be deployed with AI systems. Short for AI Safety and Governance Orchestration, asago is intended to connect the work that is now often divided among compliance teams, data […] The post Red Hat leads open-source project to automate AI governance appeared first on SiliconANGLE .
- The Sovereign AI Choice: Why Enterprises Need to Act Now
As agentic AI reshapes how enterprises operate, the businesses pulling ahead may become the ones building sovereign control into their data and AI platforms now.
- Superblocks, AWS sign multi-year deal for enterprise AI on Bedrock
Superblocks, AWS sign multi-year deal for enterprise AI on Bedrock verdict.co.uk
- HUMAIN, MOZN to deliver enterprise AI solutions for financial sector
HUMAIN, MOZN to deliver enterprise AI solutions for financial sector verdict.co.uk
- Lead Data Engineer - Physical AI Platform, Data Engineering
Lead Data Engineer - Physical AI Platform, Data Engineering Built In
- AI cloud startup Volta valued at $2.4 billion, announces $10 billion AI partnership
AI cloud startup Volta valued at $2.4 billion, announces $10 billion AI partnership Reuters
- Eight-month-old UK start-up strikes $10bn deal with Anthropic
Eight-month-old UK start-up strikes $10bn deal with Anthropic The Telegraph
- Anthropic locks in $10 billion of compute from Volta, a cloud startup that didn't exist six months ago
Anthropic is locking in $10 billion worth of computing capacity from Volta Infra Holdings, a cloud startup that's only a few months old. The article Anthropic locks in $10 billion of compute from Volta, a cloud startup that didn't exist six months ago appeared first on The Decoder .
- The AI Boom’s Latest Winner: A Brand-New Startup That Just Landed a $10 Billion Deal With Anthropic
Volta was only established at the start of this year, and yet it’s suddenly a key player in the AI game.
- Glasp MCP Connector
Search your highlights and notes inside Claude and ChatGPT
- HappyRobot lands $150M Series C to scale agentic AI for enterprise operations
HappyRobot, a company developing agentic AI for supply chains has raised $150 million in Series C funding led by Prysm Capital and co-led by Eurazeo. Existing investors a16z, Base10, Y Combinator are ...
- HappyRobot is worth $1.2 billion. Its founder says it’s just ‘getting started’
HappyRobot is worth $1.2 billion. Its founder says it’s just ‘getting started’ Fortune
- HappyRobot Series C mints FreightTech’s newest unicorn
HappyRobot has raised about $200 million in 20 months, grown 5x since its Series B, and now runs AI agents inside more than 150 enterprise customers, from DHL to LKW WALTER. The post HappyRobot Series C mints FreightTech’s newest unicorn appeared first on FreightWaves .
- Agentic AI Startup Kily Raises ₹30 Cr To Accelerate Platform Deployment
AI startup Kily has raised a ₹30 Cr ($3.2 Mn) in a funding round led by early stage VC firm…
- Agentic AI startup Kily raises Rs 30 Cr in round led by Sorin Investments
Agentic enterprise AI startup Kily has raised Rs 30 crore ($3.1 million) in a funding round led by Sorin Investments, with participation from Razorpay and Wyser Capital. The fresh capital will be used to strengthen its product capabilities, expand go-to-market operations and increase adoption among consumer brands in India. Founded in 2025 by Sankalp Mehrotra, Anurag Singh and Sharad Chitlangia, Kily develops AI agents that help brands and sellers manage operations across e-commerce and quick commerce platforms. Its platform collects marketplace data and combines it with a brand's business goals and operating requirements to automate decisions and workflows. It helps brands manage areas such as product visibility, advertising, pricing, inventory and other commerce operations across digital platforms. Kily works across e-commerce and quick commerce platforms including Amazon, Flipkart, Blinkit, Zepto and Swiggy Instamart. Since its launch, the startup has worked with consumer brands including ITC. According to Kily, its AI agents are designed to reduce the use of spreadsheets, dashboards and manual processes by automating commerce management and decision-making.
- AI Startup Kily Bags INR 30 Cr in Sorin Investments-led Round
AI Startup Kily Bags INR 30 Cr in Sorin Investments-led Round india.entrepreneur.com
- AI-Native CRM Startup Superleap Bags ₹36 Cr Led By Peak XV’s Surge
Enterprise tech startup Superleap has raised ₹36 Cr (around $4.2 Mn) in its pre-Series A funding round led by Peak…
- Former Swiggy, Zomato executives launch AI startup Profound with $1.5 Mn seed round
Bengaluru based AI startup Profound has raised $1.5 million in a seed funding round as it launched an AI powered platform for professional networking and hiring. The startup was founded by Anuj Rathi and Prashant Parashar, former product and technology leaders with experience across Swiggy, Zomato, Cleartrip, Flipkart, Ola and Walmart Labs. The seed round saw participation from angel investors including Swiggy CEO Sriharsha Majety, Swiggy cofounder Nandan Reddy, former Zomato cofounder Pankaj Chaddah, Razorpay CEO Harshil Mathur, WhatsApp Global Head Kunal Shah, and OfBusiness cofounder Bhuvan Gupta, along with venture capital firms Stellaris Venture Partners and 3one4 Capital. The company will use the fresh capital to expand its engineering and product teams, enhance its AI capabilities, and develop its matching and introductions engine. It plans to onboard one million professionals globally before opening beta access to more users. Profound offers every professional an AI powered representative that starts with a voice conversation to understand a user's experience, expertise, work style and career goals. Based on this, the platform recommends opportunities and facilitates professional introductions. The startup also enables hiring managers to create AI representatives for roles and teams, allowing companies to capture hiring requirements through voice conversations instead of traditional job descriptions. "Just as actors have agents and athletes have managers, Profound gives each professional their own AI Rep," cofounder and CEO Anuj Rathi said in a statement. The company has opened early access for its first cohort, while a wider beta launch is planned later this year.
- Vertex Growth leads X Mile’s US$21.4M Series C for non-desk workforce AI
Japan’s logistics yards, construction sites and factory floors are not usually where venture capital headlines begin. Yet they sit at the centre of one of the country’s most urgent economic questions: how to keep essential industries running as the workforce ages, labour becomes harder to find, and smaller operators struggle to modernise. Tokyo-based X Mile […] The post Vertex Growth leads X Mile’s US$21.4M Series C for non-desk workforce AI appeared first on e27 .
- Zenity secures $125m Series C funding for AI agent governance
Zenity has completed a Series C round to support its ambitions to expand globally and further develop its AI security and governance platform.
- Zenity secures $125m Series C funding for AI agent governance
Zenity secures $125m Series C funding for AI agent governance verdict.co.uk
- Obsidian Security raises $85M as AI agents create cybersecurity’s next major attack surface
Obsidian Security Inc. has raised an $85 million Series D funding round at a post-money valuation of $1.1 billion as enterprises increasingly look to secure autonomous artificial intelligence agents accessing cloud applications, Chief Executive Hasan Imam said today in an exclusive interview with theCUBE with me at our NYSE Wired studio in NYC. The round […] The post Obsidian Security raises $85M as AI agents create cybersecurity’s next major attack surface appeared first on SiliconANGLE .
- Legal AI startup Aavalynx raises £1.5M to cut the cost of corporate disputes
Legaltech Aavalynx has raised £1.5 million in pre-seed funding to help enterprises tackle the financial risk of legal disputes. Founded in 2023 and commercially live in 2024, Aavalynx has developed p...
- Paris-based Shiplog raises over €807.6K to build agentic customer intelligence for personalisation at scale
Shiplog, a Paris-based startup building agentic customer intelligence for personalisation at scale, has raised over €807.6k ($930k) in pre-Seed funding to build what it believes will become the intelligence layer behind every customer interaction on the internet. The round was backed by Kima Ventures and Project Europe, alongside Purple, No Label Ventures, 100IN and Station […] The post Paris-based Shiplog raises over €807.6K to build agentic customer intelligence for personalisation at scale appeared first on EU-Startups .
- Alibaba launches next-gen Qwen3.8 with 2.4 trillion parameters
Alibaba on Monday unveiled its next-generation foundation model Qwen3.8. The model features 2.4 trillion parameters and delivers improvements in coding and professional workplace tasks (Cowork). In the recently released third-party Arena rankings, Alibaba’s Qwen model ranked second only to Anthropic’s Claude series. The Qwen3.8 API is now available through the Qwen AI platform and has […]
- Alibaba Releases New Qwen Model, Consolidates AI Office Tools
Alibaba Releases New Qwen Model, Consolidates AI Office Tools Caixin Global
- Tech Brief (Aug. 4): Alibaba Launches New Large Model to Power Enterprise-Facing AI Agent
Tech Brief (Aug. 4): Alibaba Launches New Large Model to Power Enterprise-Facing AI Agent Caixin Global
- Alibaba Unveils Biggest Qwen Model; DeepSeek Drives AI Costs Lower
Alibaba Unveils Biggest Qwen Model; DeepSeek Drives AI Costs Lower apac.entrepreneur.com
- Computing Actual Causes for Neural Network Predictions under Structured Causal Inputs
Explaining the predictions of neural networks is a central challenge in trustworthy AI. Existing explanation methods, such as those based on feature attribution or minimal sufficient sets, typically treat input features as independent, which can yield misleading explanations when inputs exhibit stru...
- Can LLMs Test Terminal User Interfaces?
Terminal User Interfaces (TUIs) combine the stateful, screen-oriented behaviour of GUIs with terminal deployment and are now common in developer tools. Yet they lack a dedicated testing methodology. We survey 197 real-world TUI applications: only 12% of test code exercises the interface, and 45% of ...
- AI-Based Sound Effect Generation: A Narrative Review of Generative Models Across Input Modalities
Sound effects play a crucial role in conveying actions, events, and environmental cues across digital applications, often requiring a high degree of variation and contextual adaptability. Artificial intelligence (AI)-driven audio generative models are rapidly growing in popularity and have the poten...
- Failure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement
Multimodal large language models (MLLMs) have achieved remarkable performance across vision-language tasks, but their progress depends heavily on large-scale, high-quality multimodal data that are costly to annotate. Self-augmentation offers a promising alternative by enabling models to expand their...
- CARE-Bench: Benchmarking Patient-Facing LLM Triage
Patient-facing medical LLMs and agents increasingly answer symptom questions before clinician contact, where the key safety question is what action the user should take next. We introduce CARE-Bench, a source-grounded benchmark that evaluates sequential patient-facing triage as a four-label per-turn...
- GPTKB 2.0: Direct Construction of Disambiguated Knowledge Bases from Large Language Models
Automated Knowledge Base Construction (AKBC) is a core NLP task, and recent work proposes generating knowledge bases directly from large language models (LLMs), treating the model itself as the knowledge source. However, LLMs natively possess no representation of entities, leading to duplicate entri...
- When Outputs Disperse, Does Epistemic Revision Follow? A Black-Box Coupling Diagnostic for Machine Collectives
Collective intelligence research treats disagreement as evidence of epistemic diversity: if agents express different views, the group should retain capacity to revise. In LLM collectives this proxy can break: agents can produce diverse-looking arguments while preserving the same conclusion. We opera...
- Pattern over Pixels: Measuring Pattern Completion Bias in Multimodal Code Generation
Multimodal large language models (MLLMs) are increasingly used to translate webpage screenshots into front-end code, but repeated UI patterns may sway them toward visually incorrect yet pattern-consistent outputs. In this work, we test how repeated webpage patterns hurt MLLM accuracy on an objective...
- PhyAI: Real-Time Physical AI at the Edge, Scalable Rollouts in the Cloud
Physical AI policies require inference throughout their lifecycle, including model evaluation, cloud reinforcement learning rollout, edge GPU serving, and onboard deployment. Although these settings share the same checkpoint and action semantics, they often rely on separate inference programs. To un...
- space ocr
OCR that checks its own answers, as an app or an API
- Taming the Implicit: Dual-Channel Risk-Aware Reinforcement Fine-Tuning for Continual Multimodal Post-Training
Reinforcement fine-tuning (RFT) is widely believed to inherently resist catastrophic forgetting in continual post-training of multimodal large language models. Under pronounced task distributional shifts, however, forgetting across representative RFT algorithms escalates sharply. This stems from the...
- How Closely Do LLM Reviews Align with Human Peer Review?
Large language models (LLMs) are increasingly used to generate scientific reviews, yet existing evaluations rarely examine whether different providers align with both conference decisions and human reviewing priorities within the same controlled setting. We compare reviews from OpenAI GPT-5.4, Googl...
- AutoSND: From Execution Evidence to Structural Policies for Automated Network Dismantling Heuristic Discovery
Network dismantling is fundamental to analyzing the robustness and vulnerability of complex systems, yet practical heuristics must balance effectiveness and computational efficiency, and are usually designed manually by researchers. Existing large language model based automatic heuristic design meth...
- MuEvo: LLM-Driven Evolution of Multi-Heuristic Ensemble
Large language model-based automated heuristic design (LLM-AHD) has shown strong potential in discovering effective heuristics for combinatorial optimization problems. However, existing methods primarily optimize a single heuristic, whereas practical optimization frameworks often rely on multiple in...
- Unequal Verdicts: Investigating Gender Bias in LLM-Based Fake News Detection
Large Language Models (LLMs) are increasingly used for automated fact-checking, yet their susceptibility to gender bias in this context remains underexplored. This study presents the first systematic investigation of gender bias in LLM-based fake news detection using real-world data. We augment the ...
- A Security-Oriented Lifecycle Model for Large Language Model Systems
Large language models are being integrated into critical infrastructure and enterprise workflows at unprecedented scale,yet the lifecycle frameworks governing their development and operations were designed for operational efficiency rather than security analysis. As a result, security-relevant activ...
- Rethinking Modality Reliability in Multimodal Sentiment Analysis with Incomplete Observations
Multimodal Sentiment Analysis (MSA) integrates text, audio, and vision to infer human affect, yet real-world multimodal observations are often incomplete. Existing methods for incomplete-observation MSA mainly follow two paradigms. Reconstruction-based methods recover missing information from observ...
- Formal Verification of Agentic Systems over Operational Data
Agentic systems driven by large language models (LLMs) are increasingly deployed in real-world workflows where they act on persistent operational data. Before deployment, these systems need to be verified against business requirements that govern workflow execution and data evolution. However, exist...
- FraQ: Efficient Coordinate-Space Recompression for Federated Low-Rank Adaptation
Federated fine-tuning with Low-Rank Adaptation (LoRA) enables efficient collaborative adaptation of Large Language Models (LLMs) without centralizing private data. However, LoRA's two-factor parameterization creates an aggregation mismatch across clients: naively averaging the factors does not recov...
- Large language models for partial differential equation workflows
Partial differential equations (PDEs) become actionable in science and engineering not as isolated formulae, but as executable workflows that connect modelling assumptions, governing equations, numerical solvers, diagnostics, and decisions. Large language models (LLMs) are beginning to support such ...
- DiagChain: A Diagnostic Benchmark for Evaluating LLM Agents on Evidence-Grounded Attack Chain Reconstruction
Large Language Model (LLM) agents offer a promising approach to attack chain reconstruction by retrieving and interpreting heterogeneous telemetry to infer ordered attacker actions. However, existing benchmarks mainly evaluate final outputs or aggregate accuracy, providing limited insight into how e...