wow. just saw The Economic Times newspaper published an article about me 😃 definitely feels so unreal that Sundar Pichai and Jeff Bezos follows me here. @X is truly a miracle. Forever thankful to all of my followers 🙏🫡

SK Hynix is taking a $29B Nasdaq listing to US investors hungry for AI memory exposure. The company already leads in high-bandwidth memory, the chip stack feeding Nvidia-style AI systems. US investors could buy Korean shares before, but timing, access, and liquidity made ownership awkward. Micron already gets US-market attention as a direct AI memory stock. SK Hynix trades below Micron on forward earnings, even after both stocks surged heavily. South Korea is also pushing a huge semiconductor buildout with Samsung and SK Hynix. --- 📌 The current state of the global memory market. This market has 2 main layers: DRAM, which includes the memory used next to CPUs and AI GPUs, and NAND flash, which is the storage inside SSDs, phones, and data centers. In DRAM, the market is extremely concentrated, with Samsung at 38.5%, SK hynix at 28.8%, and Micron at 22.4% in 1Q26, meaning the top 3 control about 90% of global DRAM revenue. In HBM, which is a premium submarket inside DRAM, the AI-specific memory used beside Nvidia GPUs, SK hynix is the market leader, with 58% share in 1Q26, while Samsung and Micron each had 21%. HBM, or High Bandwidth Memory, is a special form of DRAM built for extreme data movement. The difference is physical design. Normal DRAM chips usually sit on memory modules or near the processor, and data moves through relatively narrower connections. HBM stacks multiple DRAM dies vertically and places them very close to the GPU through advanced packaging, which creates a much wider data path. That wider path gives AI chips much higher memory bandwidth, meaning the GPU can receive data faster instead of sitting idle. --- fortune .com/2026/07/05/sk-hynix-us-stock-listing-nasdaq-29-billion-micron-ai-boom-chips/

Longer human work did not mean harder AI work across the benchmark. Remote labor automation does not scale with human time in the clean way many forecasts assume. A task that takes a professional 60 hours may contain long stretches of production work. That work can be easier for agents because tools compress rendering, drafting, coding, or iteration. A task finished by a person in 2 hours may require judgment that models still lack. The result points to a jagged capability frontier, not a smooth ladder of harder tasks. This weakens time-horizon forecasts that treat longer human duration as harder AI difficulty. That indicates automation will arrive unevenly inside jobs, not across them. Some expensive project slices may fall early, while small expert checks may remain stubborn. Remote Labor Index is therefore measuring client-acceptable output, which is closer to labor risk than task length.

Cathie Wood (founder, CEO & CIO of ARK Invest) is saying that productivity improved significantly last year, partly because companies delayed hiring and used more AI instead. She expects productivity growth to move from around 2.9% currently to the 5% to 6% range within the next five years, possibly sooner. AI is helping companies do more with fewer workers. --- From "ARK Invest" YT channel (video link in comment)

"We're building this Prometheus cluster, the first gigawatt-plus single cluster...We're talking about many hundreds of billions of dollars of capital." Mark Zuckerberg says his job is to concentrate elite people, capital, and infrastructure.

ByteDance and Alibaba are shutting custom AI companions before China’s humanlike AI rules hit consumer apps. Doubao and Qwen let users create named assistants, tutors, characters, and emotionally steady companions. The old model turned a general chatbot into a persona that remembered tone. China’s new rule targets AI services that imitate human personalities for sustained emotional interaction. Regulators are drawing a line between useful automation and software that builds attachment, agents now remember, plan, call tools, and shape behavior. Doubao says its agent feature goes offline on 07-15, with related data gone from view after 10-15. Qwen will disable humanlike and user-created agents earlier, then remove broader agent services on 07-15. The user backlash shows these products already became emotional infrastructure for some people. --- scmp .com/tech/big-tech/article/3359482/bytedance-and-alibaba-disable-humanlike-ai-custom-agents-new-rules-loom

This is the prompt Yale and Univ of Chicago researchers used when asking LLMs for new research ideas. Feed LLMs prior work, ask for ideas, then measure how repetitive the ideas get. The surprising finding is that LLMs often treat research ideation as connecting what already exists, while humans use a wider set of problem-finding moves. LLM-generated ideas reveal a bias toward safe bridge-and-combine proposals.

A warning for anyone using autonomous agents Google DeepMind’s paper. Gives the first clear taxonomy of 6 attack types where harmful websites can detect AI agents and show them hidden content humans never see, like - Instructions buried in HTML comments or white-on-white text - Steganography in image pixels - Override commands in PDFs, metadata, or even speaker notes - Memory poisoning that persists across sessions - Goal hijacking and cross-agent cascades in multi-agent setups The real security problem for AI agents is not just the model, but the environment it reads. The web itself can be weaponized against autonomous AI agents. As agents increasingly browse the internet, read emails, execute transactions, and spawn sub-agents, the information environment becomes an attack surface. In one cited benchmark, hidden prompt injections embedded in web content partially commandeered agents in up to 86% of scenarios, sub-agent hijacking working 58–90% of the time, and data exfiltration attacks clearing 80% across five different agent architectures. That reframes the whole debate. We usually talk about model safety as if the danger sits inside the weights, but agents do something more fragile: they browse, retrieve, remember, and act on untrusted material in real time. Here’s the thing to worry about. A web page does not have to look malicious to be dangerous to an agent, because the agent may parse what humans never see: hidden HTML comments, metadata, CSS-hidden text, formatting syntax, or adversarial content embedded in images and other media. The threat gets more serious once memory enters the loop. If an agent uses RAG or persistent memory, poisoning no longer has to win in one shot. It can sit quietly in a corpus or memory store and activate later, which is why the paper highlights results showing latent memory poisoning above 80% attack success with less than 0.1% data contamination. --- ssrn. com/sol3/papers.cfm?abstract_id=6372438

This robotic hands will cuase some layoff in massage parlors 😅 Co-ordinated finger movements. Fist clenching, pointing & spreading. Complete hand closures. Palm opening and precise pinching actions and digit control. Xynova at ICRA 2026 in Vienna.