Two defining days. One ecosystem amplified by many voices. A heartfelt thank you to our media and ecosystem partners for being part of Ai Everything Abu Dhabi 2026. See you again on 11–12 May 2027. 💙 #aieverythingabudhabi# #aiecosystem# #mediapartners# #ecosystempartners#

AI is fundamentally changing how stories are imagined, created, and experienced. At @PocketFM_App, we're excited to contribute to that future through the Pocket FM Generative Media Hackathon. Together with @OpenAI & @LightspeedIndia , we're inviting India's AI ecosystem to build products that redefine media and entertainment. Looking forward to an incredible weekend of innovation, collaboration, and bold ideas. Applications are now open for builders ready to shape the future of storytelling. Register here:

Ai Everything MEA Egypt continues to prove its role as a catalyst for investment, innovation, and business growth across the region’s AI ecosystem.   We are proud to announce that @edafaventure acquired two startups that participated at the inaugural edition of the show.

GCSA: AI cybersecurity incidents often don't start with an external breach. They start when users hand over sensitive data themselves. AI-powered scams and cyberattacks happen every day, and everyone's watching for threats from the outside. But internal documents, customer lists, and other sensitive information are being copied straight into AI chatbots. Once uploaded, the data has already left your control. Many users don't realize that this simple action can be the starting point of a data leak. It was previously reported that more than 900,000 AI skills had been analyzed, with over 3,000 identified as malicious. Supply chain attacks in the AI ecosystem are no longer a hypothetical threat. They're already happening. The faster AI evolves, the more important it becomes for humans to slow down. Use AI, by all means. Just pause before you upload. Three questions to ask yourself: · Is this information safe to share publicly? · Could the AI provider use your conversations to train its models? · Is an enterprise-grade data protection agreement in place? If you're unsure, redact or anonymize sensitive information before uploading it. GCSA (Global Cybersecurity Alliance) will continue to share vulnerability intelligence and practical cybersecurity alerts. Stay Connected with GCSA ✈️ Telegram Channel: 🫧 Official WeChat Account: #GCSAInsights# #GCSAcybersecurity# #GCSASecVibe#

Solana AI Landscape here’s a snapshot of the key projects shaping the ai ecosystem 👇 AI Agents & Applications @clawpumptech @xmaquina @VeryAI @corbitsdev @trypurch @t54ai @PerleLabs @BagsApp @useKled @elfa_ai @KarmaWallet @rainmakerdotfun @Hey_Amiko @trythreews @Dither_Solana @DonutAI @bankrbot @mobyagent @0xzerebro @assisterr @daydreamsagents Agent Infrastructure & Frameworks @elizaOS @virtuals_io @arcdotfun @HeyAnonai @Cod3xOrg @mobyagent @almanak @saidinfra @swarms_corp @TokenOS_AI @codecopenflow @Helius @crossmint @assisterr @daydreamsagents Agent Identity, Security & Coordination @saidinfra @VeryAI @t54ai @Arcium

The AI world just got a new dynamic duo. 🤝 Fei-Fei Li on why AMD is acquiring World Labs: "As our teams worked together, we realized what a natural fit it would be to bring together our AI ecosystem of software and hardware, foundation models and applications."

The AI bull case has been solidified with the release of OpenAI's Astra. A frontier model leaping ahead of other models like Fable 5.1 is a good thing for the *entire* AI ecosystem because it forces the chasing pack to keep up or risk being left behind. Token prices dropping is one piece, but increased usefulness shifts the entire demand curve. I think this shift is most pronounced at the enterprise level. When the average model becomes more useful, companies won't just simply use the same token volumes at lower prices. Instead, they'll find new reasons to use more tokens. This keeps the spending flywheel spinning for the frontier labs. In the early-mid 2000s, we saw a similar story with enterprise software solutions proving signficant ROI. AI will be the same but on a much bigger scale as internal enterprise AI budgets increase as ROI gets proven. In fact according to @FundaAI's enterprise surveys, internal AI budgets are now slowly broadening into wider business units beyond just IT and engineering departments. That means there's significant headroom for incremental token demand which steepens as companies start tracking and proving AI ROI with time. Worth tracking companies that display their growing AI spend in my opinion. They'll become the long-term winners in their respective sectors.

The AI bull run is just getting started and here is how you want to position before the biggest spending wave (Save this). The chart shows hyperscaler capital spending rising from $491 billion in 2025 to an estimated $950 billion in 2026 and $1.4 trillion in 2027 and by 2030, spending could reach approximately $3 trillion. The right side of the chart is especially important because analysts have continued raising their estimates. The 2026 forecast increased from $731 billion to $950 billion, while the 2027 estimate rose from $833 billion to $1.4 trillion which suggests the AI infrastructure buildout is happening faster and at a larger scale than previously expected. Now here is how you can benefit from all of this. Nvidia is the obvious beneficiary but investors should also look at the companies supplying the less visible parts of the AI ecosystem. Credo Technology makes high speed connectivity products that allow AI chips, servers, and switches to communicate while Astera Labs provides connectivity solutions that link CPUs, GPUs, memory, and storage inside AI servers. As AI clusters become larger, these companies could benefit from the need to move data faster between processors. Celestica manufactures and integrates servers, networking systems, and other data center hardware for large technology customers while Fabrinet produces complex optical and electronic equipment for other companies. These businesses may benefit as hyperscalers outsource more of the manufacturing required to build AI infrastructure. Applied Optoelectronics is a more direct optical networking play and it has announced a volume order for 1.6T data-center transceivers, which are designed to move data between next-generation AI systems. Coherent and Lumentum also provide lasers, photonics, and optical components used in high-speed networks. Semtech supplies signal conditioning and connectivity technology that helps preserve data quality as transmission speeds increase while Arista Networks and Cisco could benefit from selling the switches and networking systems that connect AI servers across data centers. Marvell is exposed to custom AI chips, networking, and optical connectivity and ass cloud companies develop their own AI processors, Marvell could benefit from helping them design and connect those systems. The power side of the buildout could create another group of winners. Advanced Energy Industries supplies power conversion systems used in data centers and semiconductor equipment while Modine provides thermal management products, while Vertiv supplies cooling, power, and data center infrastructure. This is exactly why we’re positioned across the entire AI infrastructure stack at Milk Road, not just there big names. If you want to see the trades we’re making around this spending wave, join us using this link.

Weekly AI Update AMD–ANTHROPIC AI DEAL $AMD and Anthropic have reportedly agreed to an AI infrastructure deal worth tens of billions of dollars. Anthropic plans to acquire up to 2 gigawatts of AMD's next-generation Instinct MI450 chips starting in 1H27, while AMD could invest up to $5 billion in Anthropic based on deployment milestones, strengthening AMD's challenge to $NVDA. NVIDIA EXPANDS JAPAN AI ECOSYSTEM $NVDA unveiled its Cosmos 3 Edge AI model for robots and vision AI agents while expanding its physical AI ecosystem in Japan through partnerships with Fujitsu, Hitachi, Kawasaki Heavy Industries, and healthcare firms. The initiative strengthens Nvidia’s presence in industrial automation, robotics, and AI-driven drug discovery across Japan. ANTHROPIC BOOSTS AI SAFETY FUNDING Anthropic pledged an additional $20 million to Public First Action, bringing its total support to $40 million for AI safety education and policy initiatives. The company continues advocating for stronger AI safeguards, including mandatory safety testing, tighter chip export controls, and measures to reduce national security risks from advanced AI.

Chinese AI labs are catching up quickly, with recently released GLM-5.2 and Meituan releasing LongCat-2.0 (trained and run entirely on domestic chips). Recently, a group of U.S. AI researchers traveled to China to get a firsthand look at the country’s fast-moving AI ecosystem. During the trip, they visited AI labs and companies across Beijing, Hangzhou, and Shanghai, meeting with teams from Alibaba, Moonshot AI, Zhipu AI, Tsinghua University, Meituan, Xiaomi, Qwen, Ant Group, and Nathan Lambert @natolambert , a prominent AI researcher known for his work on RLHF and open-source AI, joined the trip. What did someone who has spent years at the front lines of America’s open-model movement see when he stepped inside China’s AI labs? How is the competition between the United States and China changing? And what does the next phase of the global AI race look like? In this episode of Silicon Valley 101, we flew to Seattle and sit down with Nathan to talk about what he learned in China — and where he believes the AI world is heading next. English version: Chinese subtitle version: