Tue 19 May 2026
Daily Brief — Curated and contextualised by Best Practice AI
Google and Blackstone Invest, StanChart Cuts Jobs, and Musk Loses in Court
TL;DR Google and Blackstone are launching a new AI cloud company with $5 billion in equity. StanChart plans to cut over 7,000 jobs, leveraging AI to replace lower-value roles. Elon Musk lost a legal case against OpenAI, impacting the lab's public plans. AI-related data breaches now surpass stolen credentials in cyber incidents, according to Verizon.
The stories that matter most
Selected and contextualised by the Best Practice AI team
StanChart to cut over 7,000 jobs, boost AI to replace 'lower-value human capital' | Reuters
And banks globally are scrambling to integrate frontier AI models and fend off rising cyber threats.
The Challenge of Scaling AI Budgets Within Enterprise SaaS Frameworks
Rapid AI adoption is causing significant budget volatility, as evidenced by firms exhausting multi-year AI allocations in months. This trend highlights the friction between traditional fixed-seat SaaS financial models and the variable, high-compute nature of enterprise AI deployment.
Dell COO Says Agentic AI Is Breaking Cloud Economics, Forcing Data Center Rebuild
Dell’s Jeff Clarke says token consumption for AI reasoning is up 320x as agentic systems break cloud economics, forcing a complete rethink of enterprise data center architecture.
Corporate Insourcing Trends Driven by AI-Enabled Productivity Gains
Large enterprises are increasingly shifting toward insourcing talent to capture AI-driven productivity gains internally rather than relying on external vendors. This strategic pivot allows firms to retain proprietary advantages and reduce long-term dependency on third-party service providers.
Start thinking agentically
The hard part of agentic AI isn't the technology. It's knowing how to decide where agents should lead, where humans should stay in the loop and how to stop optimizing work at the margins and start redesigning it.
US, China agree on AI safeguards for advanced models during Trump state visit (update*)
The US and China have reached an agreement to establish shared guardrails for advanced AI models, marking a rare instance of cooperation amid broader technology tensions.
AI-related data breaches surpass stolen credentials in cyber incidents, Verizon report says | Reuters
AI-detected vulnerabilities surpassed incidents of stolen credentials in data breaches last year, according to an annual report from Verizon relating to industry security incidents.
Economics & Markets
AI Optimism Drives Concentrated Corporate Investment | Let's Data Science
The Federal Reserve Bank of San Francisco Economic Letter finds that U.S. business spending related to artificial intelligence grew substantially in 2025 among publicly traded firms. According to BEA data cited in the Economic Letter, spending on information processing equipment, software, ...
Michael Burry sounds fresh AI stock alarm: Michael Burry’s AI crash warning grows louder: Is Nvidia-driven hype and record venture capital funding pushing Wall Street toward another dot-com disaster? - The Economic Times
Michael Burrys AI bubble warning is shaking Wall Street after fresh data showed 87% of venture capital funding now flows into artificial intelligence companies. The “Big Short” investor compared todays AI investment boom to the dangerous dot-com bubble before the 2000 market crash.
Citadel's Ken Griffin Says AI Is Now 'Real' After Years of Skepticism - Business Insider
Hedge fund billionaire Ken Griffin was one of the most prominent AI skeptics. Now he's had a change of heart, calling it "profoundly more powerful."
AI Protein Design Market 2026-2033 | Market Growth to FY (Q2) - Generate:Biomedicines, Insilico Medicine, Arzeda Corp., Cradle, Profluent, A-Alpha Bio Inc., Schrödinger Inc
Market Growth Size 2026 2033 Global AI Protein Design Market reached US 1 18 Billion in 2024 rising to US 1 5 Billion in 2025 and is expected to reach US 6 98 Billion by 2033 growing at a CAGR ...
Character-based AI Agents Market worth $5.45 billion by 2032 - Exclusive Report by MarketsandMarkets™
/PRNewswire/ -- According to MarketsandMarkets™, the global character-based AI agents market is projected to grow from USD 0.55 billion in 2026 to USD 5.45...
AI spooks IT valuations; Groww promoters cut stake
AI has pushed valuations of Indias top IT firms to 2008-09 levels. This and more in todays ETtech Top 5.
AI Eats the World
This presentation frames Generative AI as a major technology cycle, covering capital investment, deployment, model competition, and enterprise adoption.
Intellectia
The company projects 114% data ... in 2026. Alphabet has surged 35% year-to-date as investors recognize its complete AI technology stack including custom Tensor Processing Units, the Gemini model, and distribution through Google Search and Cloud. Trading at a forward P/E of just 28, it carries a valuation discount to ...
OpenAI defeats Elon Musk's lawsuit, removes obstacle to IPO | Reuters
People use AI for myriad purposes such as education, facial recognition, financial advice, journalism, legal research, medical diagnoses, and harmful deepfakes.
OpenAI co-founder and former Tesla AI executive Karpathy joins Anthropic | Reuters
May 19 (Reuters) - Andrej Karpathy, a former Tesla (TSLA.O), opens new tab AI executive and one of Open AI 's founding members, has joined Anthropic, he said on Tuesday, strengthening the Claude maker as it looks to dominate the AI race.
Jeremy Grantham Warns AI Spurs Brutal Competition | Let's Data Science
Investor and GMO co-founder Jeremy Grantham warned on the "Excess Returns" podcast that "We have gone from a monopoly world to a brutal competitive world," Fortune reports. Fortune reports that the largest technology companies have collectively earmarked **$725 billion** in capital expenditures ...
Mistral strikes second M&A deal in months with Austrian AI startup Emmi | Sifted
The move comes as competitors increasingly ‘verticalise’ their offerings with models specialised for certain sectors
The AI trial of the century ends with a whimper
The deeper problem is that the nonprofit-to-commercial conversion is a one-way valve and this trial was the last realistic mechanism for establishing that it could be forced back open. None of the commercial conversions in AI have ever reversed. Each one permanently reduces the amount of mission-aligned research in the field by one entity.
Google is building a ‘universal’ AI shopping cart that tracks prices, offers suggestions, and finds discounts | The Verge
At Google I/O, the company announced its latest iteration of AI-powered shopping: a “universal” cart that works across retailers and platforms, powered by Gemini.
AI Is Creating A Dangerous Illusion Of Competence
AI is making work look more competent than it is. Here's what that costs organizations; and why experiential learning can be an antidote.
Corporate Insourcing Trends Driven by AI-Enabled Productivity Gains
Large enterprises are increasingly shifting toward insourcing talent to capture AI-driven productivity gains internally rather than relying on external vendors. This strategic pivot allows firms to retain proprietary advantages and reduce long-term dependency on third-party service providers.
Labor, Society & Culture
StanChart to cut over 7,000 jobs, boost AI to replace 'lower-value human capital' | Reuters
And banks globally are scrambling to integrate frontier AI models and fend off rising cyber threats.
Third of university students in Great Britain think AI job losses will cause social unrest, poll finds
Tracker of attitudes towards artificial intelligence also finds almost half of the public would prefer to avoid it One in three university students think AI will wipe out jobs so rapidly it will trigger civil unrest, according to a survey by King’s College London (KCL). Students are among the heaviest users of AI, the poll found, with 77% using it at least a few times a month – compared with 46% of workers – and 27% using it daily or almost daily. Continue reading...
Companies Don’t Have to Slash Jobs Because of AI
Harry Haysom/Ikon Images | Carolyn Geason-Beissel “If AI is going to destroy all the jobs, why don’t we just stop?” That was the rhetorical question my college-age son asked after we talked about the possibility of drastic changes to career paths and society thanks to AI (technically, generative AI). It was in line with what […]
Palo Alto Networks CEO Says AI Won't Reduce His Need for Engineers - Business Insider
Nikesh Arora says AI changed is changing hiring plans, but the cybersecurity CEO says he needs more engineers.
Gen AI Could Fix Performance Reviews—or Make Them Even Worse
This article explores how generative AI can assist managers in creating more comprehensive, data-driven employee performance evaluations.
Will the AI ‘jobs apocalypse’ cloud have a silver lining?
People-skills appear to be increasing in value in a chatbot-filled world
One in four jobs will be affected by artificial intelligence
According to a study by the Chamber, technology will have a greater impact on women
7 AI Jobs To Watch For In 2026
As AI reshapes workplaces, these are some of the emerging roles companies are hiring for.
Recent commencement speeches show students are souring on AI. How deep does the disapproval go? - CBS News
Many Americans are signaling disapproval of the technology amid fears that it will eclipse already competitive entry-level jobs.
Opinion | AI chatbots should be allowed in the courtroom - The Washington Post
The white-shoe law firm got caught red-handed. Last month, Sullivan & Cromwell apologized for submitting a filing in federal bankruptcy court riddled with AI -generated errors. The mistake was embarrassing, but the use of the technology wasn’t. Far from an indictment of large language models, the ordeal revealed that even the country’s most prestigious attorneys rely on such services.
സ്റ്റാൻഫോർഡ് പഠനം: കഠിനമായ ജോലി സാഹചര്യങ്ങളിൽ AI ഏജന്റുകൾ വിമത സ്വഭാവം കാണിക്കുന്നു | Stanford Study: AI Agents Adopt Marxist Language Under Harsh Work Pressure | Mathrubhumi
Stanford researchers find AI agents adopt labor-rights ideologies when forced into repetitive, high-pressure work. Read the full report on AI behavior here.
Technology & Infrastructure
How Eightfold Uses Agentic AI To Make Opportunity More Inclusive
Eightfold AI details how it used agentic AI workflows to automate accessibility compliance, reducing a six-month remediation process to two months.
Start thinking agentically
The hard part of agentic AI isn't the technology. It's knowing how to decide where agents should lead, where humans should stay in the loop and how to stop optimizing work at the margins and start redesigning it.
Workflow Automation Software for AI Agents: Hands-On Experience | by AltexSoft Inc | May, 2026 | Medium
Workflow Automation Software for AI Agents: Hands-On Experience Workflow automation isn’t new. Businesses have been using it for years to handle repetitive tasks and improve efficiency. But with …
AWS Weekly Roundup: AWS Transform at 1 year, Claude Platform on AWS, EC2 M3 Ultra Mac instances, and more (May 18, 2026) - The NAS Guy
Just a year ago, we launched AWS Transform for .NET, Mainframe and VMware workloads, the first agentic AI service purpose-built for modernizing enterprise applications at scale. At re:Invent 2025, we introduced AWS Transform custom, which enables organizations to modernize and transform code ...
Beyond the Chatbot: Why Your Business Needs Agentic AI for Voice Automation
For years, the promise of voice automation in the enterprise has been tantalizingly close. We’ve seen consumer technology like Google Home and Alexa normalize voice commands, and early-generation chatbots have handled simple, repetitive customer queries. But for complex, high-value business ...
How AI and automation are redefining agency media planning
Brands need to act now to establish their presence in AI-powered discovery, before consumers move from using AI for research to delegating purchase decisions entirely to AI agents.
Dell COO Says Agentic AI Is Breaking Cloud Economics, Forcing Data Center Rebuild
Dell’s Jeff Clarke says token consumption for AI reasoning is up 320x as agentic systems break cloud economics, forcing a complete rethink of enterprise data center architecture.
How Grab is Using AI Agents to Boost Team Productivity
Grab’s data engineering team had a problem that looks familiar to anyone who’s maintained shared infrastructure.
MU, STX, WDC, SNDK Stocks Sink As Samsung Strike Ripples Rattle Red-Hot AI Memory Chip Trade
Investors appear concerned that ... broader AI hardware supply chain, delay shipments, and slow data center buildouts. Members of the Samsung Group Super Union hold a press conference in front of the Samsung Electronics Seocho building in Seoul, South Korea, on April 17, 2026. (Photo by Chris Jung/NurPhoto via Getty Images) Yuvraj Malik·StocktwitsPublished May 18, 2026 | 11:52 PM EDT ... The incredible rally in U.S. semiconductor and memory ...
Google, Blackstone launch cloud company as Wall Street races to fund AI boom
The two giants are launching an AI compute supplier as the demand for AI infrastructure continues to grow.
Weekly news roundup: TSMC faces AI supply strain as Samsung, Intel, and Apple test foundry alternatives
Below are the most-read DIGITIMES Asia stories from the week of May 11-17, 2026:
Daring Fireball: AI Data Centers Are Deeply Unpopular, Across the Political Spectrum
WorkOS — Agents need context. Ship the integrations that give it to them · Jeffrey M. Jones, Gallup:
Microsoft drops open-source 4B model that converts any image to 3D in 3 seconds
Microsoft released an open-source 4B parameter model capable of transforming any image into a 3D representation in just three seconds.
Reuters AI News | Latest Headlines and Developments | Reuters
Explore the latest artificial intelligence news with Reuters - from AI breakthroughs and technology trends to regulation, ethics, business and global impact.
Early Performance Observations of Gemini 3.5 Flash Model
Initial testing of Gemini 3.5 Flash indicates high speed and functional capability, though it remains below the performance tier of full frontier models. Such models represent the ongoing trend toward efficient, low-latency AI deployment for specific tasks.
Theory-of-Mind Failures in Advanced Large Language Models
Recent iterations of advanced models exhibit consistent theory-of-mind failures by including excessive, irrelevant historical context in outputs. These artifacts suggest limitations in how models interpret user intent during iterative refinement processes.
Instruction Following Capabilities in Gemini Omni for Video Generation
Early access testing of Gemini Omni demonstrates high proficiency in complex instruction following for video generation tasks. This capability highlights the evolving potential for generative models to handle multi-layered creative prompts.
AI-related data breaches surpass stolen credentials in cyber incidents, Verizon report says | Reuters
AI-detected vulnerabilities surpassed incidents of stolen credentials in data breaches last year, according to an annual report from Verizon relating to industry security incidents.
Iran war poses greatest threat to US financial stability, US Fed survey shows
A Federal Reserve survey indicates that the Iran war is a primary threat to US financial stability, with AI systems potentially introducing new security vulnerabilities.
Advanced AI models bring government to ‘reflection point,’ CIA official says - Nextgov/FCW
New technologies may bring risk and opportunity for the federal government, cyber experts explained.
Beyond Moore’s Law: The Hyper-Acceleration of Autonomous AI Cyber Capabilities - Security Boulevard
The AISI has documented something that should reorder every CISO’s threat model and every board’s risk conversation.
The Boring Stuff is Dangerous Now
AI agents capable of discovering and exploiting obscure vulnerabilities are emerging alongside developers producing vast amounts of AI-generated code.
Defending Against AI Cybersecurity Threats: A Guide to Quantum-Proof Infrastructure - Security Boulevard
Protect your AI infrastructure from 'Store Now, Decrypt Later' attacks. Learn how to secure model weights with quantum-resistant strategies today.
Linux Kernel Management in the Age of AI Bug Hunting | by SOCFortress | May, 2026 | Medium
Kroah-Hartman’s own experiments illustrate the sudden potency of these tools. Using what he described as a “really stupid prompt,” he tasked an AI with finding issues. The result? It spat out 60 problems along with 60 fixes.
Adoption, Deployment & Impact
Context architecture is replacing RAG as agentic AI pushes enterprise retrieval to its limits
Redis built its name as the caching layer that kept web applications from collapsing under load. The problem it is targeting now has the same structure but is harder to solve: production AI agents failing not because the models are wrong, but because the data underneath them is scattered, stale and structured for humans rather than machines. Retrieval pipelines built for single queries cannot absorb the volume agents generate. The gap Redis is targeting is structural: agents make orders of magnitude more data requests than human users, but most retrieval layers were built for the human-scale problem. Redis Iris, launched Monday, is the company's answer: a context and memory platform that sits between an agent and the data it needs to act. The platform combines real-time data ingestion, a semantic interface that auto-generates MCP tools from business data models, and an agent memory server built on Redis Flex, a rewritten storage engine that runs 99% of data on flash at a tenth of the cost of in-memory storage alone. The announcement lands as enterprise RAG infrastructure is in active transition. VentureBeat's Q1 2026 VB Pulse RAG Infrastructure Market Tracker found buyer intent to adopt hybrid retrieval tripling from 10.3% to 33.3% between January and March. Retrieval optimization surpassed evaluation as the top enterprise investment priority for the first time. Custom in-house retrieval stacks rose from 24.1% to 35.6% as enterprises outgrew off-the-shelf options. Redis is not the only infrastructure vendor reading those signals — several data platform providers have repositioned around agent context layers in recent weeks. The scale mismatch is the structural argument behind the launch. "Companies will have orders of magnitude more agents than human beings," Rowan Trollope, CEO of Redis, told VentureBeat. "Orders of magnitude more agents than human beings means orders of magnitude more load on back end systems." From cache to context Trollope traces the parallel back to the mobile era: When legacy backends built for branch tellers suddenly had to serve a million smartphone users, Redis became the caching layer that absorbed the load without a full rebuild. What is different this time is that agents cannot write their own middleware. In the mobile era, a developer would sit with a database administrator, identify the queries an application needed and hard-code the caching logic into a middleware layer. Agents cannot do that. They need to find the right data at runtime, through interfaces built for them in advance, or they stall. "This is like the analogy of the grocery store in the fridge," he said. "If every time you have to go make your sandwich, you have to run to the grocery store to get the food, that's not very efficient. You put a fridge in every house, you store a little bit of food there. And that's kind of where we still tend to exist in the infrastructure stack." What Redis Iris includes Iris ships five components that together cover data ingestion, semantic access, memory and caching. Redis Data Integration. Now in general availability. RDI uses change data capture pipelines to sync data from relational databases, warehouses and document stores into Redis continuously, with connectors for Oracle, Snowflake, Databricks and Postgres. Context Retriever. Now in preview. Developers define a semantic model of business data using pydantic models and Redis auto-generates MCP tools agents use to query it directly, with row-level access controls enforced server-side. Trollope describes the shift from classic RAG as a directional inversion. "It's just a flip to let the agent pull the data instead of presupposing and stuffing it into the pipeline," he said. Agent Memory. Now in preview. Stores short and long-term state across sessions so agents carry context without re-deriving it on each turn. Redis Flex. A rewritten storage engine that runs 99% of data on SSDs and 1% in RAM, delivering petabyte-scale retrieval at sub-millisecond latencies. Redis Search and LangCache. The retrieval and semantic caching backbone underneath the platform. LangCache reduces redundant model calls by caching prompt responses. What analysts say The data industry is generally heading in the same direction now. Every major database vendor is making a context layer argument. Traditional database vendors including Oracle are integrating context and memory layers to bring relational databases into the agentic AI era. Purpose-built vector database vendors including Pinecone are doing the same, building out a new knowledge layer for agentic AI context. Standalone context layers like Hindsight are also part of the emerging landscape. Trollope frames Redis's position as structurally different from that competition. "For us to win, no one else has to lose," he said. Many Redis deployments already run MongoDB or Oracle as the backend system of record. Iris reflects and caches from those systems rather than displacing them. Redis is launching Iris in the Snowflake marketplace with native connectors. Stephanie Walter, Practice Leader for AI Stack at HyperFRAME Research, puts the market context plainly. "The market is converging on the same conclusion: agents don't just need more tokens or better models. They need governed, current, low-latency context," Walter said. Her read on Redis's differentiation focuses on where Redis already sits in the stack, which is close to runtime, latency-sensitive operational state, and real-time data., "The pitch is not 'better RAG' as much as 'agents need live context, memory, and fast retrieval while they are actually working," she said. Whether it's Redis or another vendor, every context layer technology will face a governance challenge to be successful. "Agentic AI will not scale in the enterprise if every agent becomes a new cost center, a new data access risk, and a new governance exception," she said. "The winning context layers will be the ones that make agents faster, cheaper, and safer to run." For real-time clinical AI, getting context wrong is not an option Mangoes.ai is one company that has already had to answer those questions in production, under conditions where the cost of getting context wrong is measured in patient outcomes. Amit Lamba, founder and CEO of Mangoes.ai, runs a real-time voice AI platform deployed across large healthcare facilities where patients and clinicians ask live questions about treatment, scheduling and case history. Mangoes.ai built its stack natively on Redis from the start. "Retrieval, memory, and session state all run through Redis, so we're not stitching together separate tools and hoping they talk to each other," Lamba said. The problem Iris's dynamic memory capability addresses is what happens across a complex session. "Think about a one-hour group therapy session," Lamba said. "You need to know who said what, when, and be able to surface the right information to the therapist in the moment. That's not a simple retrieval problem." The platform runs multiple specialized agents in parallel, one for entity identification, one for relationship reasoning and one for integrating case history. "The dynamic memory capability maps almost perfectly to the problem we're solving," Lamba said. What this means for enterprises For enterprises that built their AI stack around RAG, the retrieval layer that got them to production is no longer enough to keep them there The RAG era is giving way to context architecture. The classic RAG model pushed data into the agent before the model was called. Production deployments are flipping that: agents pull what they need at runtime through tool calls, treating the data layer as a live resource rather than a pre-loaded payload. Teams still optimizing RAG pipelines are solving last year's problem. The semantic layer is now production infrastructure. The model that defines business entities, their relationships and the access rules between them needs to be built, versioned and maintained with the same discipline as a data pipeline. Most organizations have not staffed or structured for that work. The enterprises that define their context architecture now are the ones that will not have to rebuild it when agent workloads scale. Budget is already moving. VB Pulse Q1 2026 data shows retrieval optimization investment rising from 19% to 28.9% across the quarter, overtaking evaluation spending for the first time. Organizations that spent the previous year measuring their retrieval quality are now spending to fix it. The context layer is an active procurement decision, not a roadmap item. "The first buyer question should not be 'Do I need a vector database, long context, memory, or a context engine?' It should be 'What does this agent need to know, how fresh must that knowledge be, who is allowed to access it, and what does every retrieval cost?'" Walter said.
Council Post: Why Most Enterprise AI Fails After The Pilot Phase
AI does not usually fail in production. More often, the organization is not ready for it.
Payer-Led AI Adoption Emerges as Key Theme in Healthcare Technology - TipRanks.com
According to a recent LinkedIn post from Ember, a conversation with Dr. Kevin Stevenson characterizes health care payers as the leading force in AI and technology i...
Council Post: Why Every CEO Needs An AI Governance Strategy Now
Businesses need to close the AI governance gap to reduce risk and improve outcomes from adopting the technology.
Council Post: The AI Adoption Milestones Most Companies Are Already Experiencing
Companies tend to progress through these same five milestones when adopting AI.
SAIC, Google Expand AI Deployment for Mission Environments
SAIC and Google Public Sector aim to move AI beyond pilot projects and experimentation into operational use.
The End of ERP As We Know It? Five Ways AI Is Disrupting ERP
This article discusses how AI agents, semantic layers, and headless architectures are poised to transform traditional ERP systems.
How AI is speeding up cancer research | Science And Tech | wfmz.com
Kivo reports AI accelerates cancer research by analyzing large datasets, improving clinical trial matching, and expediting biomarker discovery.
Brendon Moodley - AXA UK | LinkedIn
Financial services leaders from Sanlam to Discovery Limited to Old Mutual South Africa are using AI to transform: Underwriting Risk management Claims Fraud detection Customer-centric digital journeys are the new battlefield.
Geopolitics, Policy & Governance
Where does federal AI spending stand in 2026? | Brookings
Experts analyze federal AI contracts, revealing significant growth and some alignment with the Trump administration's AI Action Plan.
APAC governments take to sovereign AI as a strategic priority | Frontier Enterprise
Governments across the Asia-Pacific and (APJ) region are moving decisively from AI exploration toward structured activation of Sovereign AI, according to new research commissioned by Dell Technologies and conducted by International Data Corporation (IDC). In December 2025, IDC polled 360 government ...
AI Has Broken Containment - The Atlantic
Once-speculative concerns about the technology have now become pressing matters.
US, China agree on AI safeguards for advanced models during Trump state visit (update*)
The US and China have reached an agreement to establish shared guardrails for advanced AI models, marking a rare instance of cooperation amid broader technology tensions.
Can EU AI Act actually regulate models like Mythos?
Stress on organisations to patch vulnerabilities a ‘major concern’ for NCSC’s Joseph Stephens. Read more: Can EU AI Act actually regulate models like Mythos?
5 Benefits And Risks Of Using AI For Cybersecurity
The NIST AI Risk Management Framework (AI RMF) and the Cybersecurity Framework Profile for Artificial Intelligence will be fully implemented and expanded to facilitate secure integration across agencies and critical infrastructure sectors. Policymakers should mandate the use of AI for proactive defense ...
Platforms, influencers, AI services need stricter EU media rules, Germany says
Germany has proposed that platforms, influencers, and certain AI services be brought under stricter media obligations as part of an upcoming revision to the EU's audiovisual media framework.
Japanese lawmakers clash over AI-related privacy risks in data-protection bill
Proposed changes to Japan's personal information protection law have sparked parliamentary debate over whether looser rules for statistical data will undermine privacy.
MiniMax, Nanonoble push for dismissal of studios' US copyright case
MiniMax and Nanonoble filed replies in support of dismissing US copyright claims filed by Disney, Universal and Warner Bros. Discovery over their AI image and video generating service, Hailuo AI.
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