Browse Comments — Raw (as collected)

Its foss??

This is fascinating! What are your thoughts on the biggest hurdles to achieving true "world understanding" with models like Omni?

Demis Hassabis Regarding the safety of agentic systems and the deployment of CodeMender: While software-layer vulnerability detection is advancing rapidly, the foundational cryptographic assumptions securing these systems remain mathematically vulnerable to future quantum computation. To address the hardware and cryptographic layer, the Temporal Rotation Security Protocol (TRSP v3) and its digital infrastructure extension (TDC) were published today as Open Prior Art (DOI: 10.5281/zenodo.20332811). TRSP proposes shifting the security parameter from mathematical complexity to physical law. It utilizes local hardware entropy and orbital relativistic time dilation to generate ephemeral keys that are physically destroyed within a millisecond window. By casting time-irreversibility directly into silicon via destructive readout mechanisms, the architecture structurally eliminates the "Harvest-Now-Decrypt-Later" vector. As DeepMind builds the long-term infrastructure for AGI, I respectfully ask: would a physics-grounded, time-irreversible cryptographic anchor be a relevant addition to the hardware safety architecture of your agentic systems?

Very interesting way of looking at it.

I hold the keys ...

What stands out is how quickly the stack is converging around three core capabilities simultaneously: multimodal world modeling, persistent agentic execution, and scientific reasoning acceleration. The interesting shift is that these are no longer isolated research tracks. Models are increasingly being designed to perceive, reason, act, and validate across environments as part of a unified operational system. SynthID adoption is also more important than it initially appears. As world models and generative systems scale, provenance infrastructure becomes foundational for maintaining trust across digital ecosystems. The path toward AGI may depend as much on orchestration, governance, and systems reliability as on raw model intelligence itself.

What's remarkable is that the people who've spent decades pursuing AGI are now the most measured about it, not because the excitement faded, but because the weight of what's coming has grown clearer. Every I/O reveal is a reminder that we're not building software anymore, we're negotiating with the future.

Demis Hassabis As a software engineer who dreams of one day joining Google, I find these ambitious visions for AGI truly inspiring. What impresses me is not only the incredible technological advancements but also the simultaneous commitment to transparency, safety, and ethical frameworks, as exemplified by SynthID and CodeMender. Working in an environment that combines bold innovation with a responsibility to humanity is a dream come true. I hope to one day be part of this team that is writing the history of AI, not as a spectator but as a contributor to building the foundations of Singularity safely and effectively.

This is a major signal. What is emerging is not only a new generation of models, but a more integrated operating layer for AI: search, coding, science, content, agents, security, payments and user environments beginning to converge. That makes the governance question deeper than capability. As AI systems become more agentic and more embedded across everyday tools, institutions and users will need clear answers about data access, permissions, traceability, accountability and the ability to interrupt, contest or reverse action. The path toward more capable AI will also depend on whether governance can scale with the environments in which these systems operate.

I tested Gemini Omni Flash last night and I was truly impressed. Made a video of one of my PCs just by giving it a few pictures and asking it to combine everything into a smooth ad.

How do you know it's Information Theory??? 👀

Dr.Mohamed Nagy I do not think AI is a tool anymore because of the autonomy it now has

Did anyone mention how to secure all of these? Maybe run them by mythos 😁

Incredible pace of progress and some genuinely important breakthroughs especially around multimodal reasoning, agentic execution, scientific acceleration, and AI safety instrumentation. But the largest enterprise gap is no longer only model capability. The harder unsolved problems are operational governance, sovereign execution control, cross-agent state synchronization, runtime observability, operational memory consistency, real-time workflow orchestration and trusted enterprise execution boundaries That is where the industry still lacks mature operational foundations. Models are rapidly becoming more capable. Enterprise operational coherence is not scaling at the same pace. This is precisely where AI-native operational systems like MonkDB can play a major role by acting as the continuously synchronized operational intelligence layer across agents, workflows, telemetry, governance, memory, and enterprise execution systems.

The Fragmental Overlap Storage System

Thank your for making all Googlers proud of being here

What feels especially important is that AI progress is no longer advancing along a single axis of model capability. The frontier is now moving across multiple layers simultaneously: multimodal world understanding agentic coordination scientific discovery security infrastructure workflow integration institutional adoption That changes the nature of the race entirely. The organizations that shape the next era likely will not just build the most capable models. They will build the systems that organizations, governments, and individuals can reliably integrate into real-world decision-making over long periods of time. Capability matters. But trust, interoperability, coordination, and societal absorbability may matter even more.

I’m amazed by everything you’ve done, including your well deserved Nobel Prize, and have followed your podcasts/interviews since AlphaGo. There is genuine optimism in your vision of an “age of abundance.” But should we worry about the transition path? History suggests major tech revolutions create enormous wealth concentration before benefits spread. The Industrial Revolution improved billions of lives — but only after decades of inequality and social upheaval. This AI wave feels like tech change on chip steroids — both in scale and speed. Even today, we already see concentration of value creation around a relatively small number of companies, countries and ecosystems. If AGI becomes “10x bigger and 10x faster” than previous tech revolutions, the risk may not only be job displacement, but widening inequality — within countries, between capital and labor, and between advanced AI nations and the developing world. Will the “age of abundance” become genuinely inclusive — or risk becoming a mirage where much of humanity cannot participate in its benefits? Perhaps the challenge of this century is not whether we can build AGI, but whether we can ensure its benefits are shared broadly — while limiting misuse by bad actors.

Powerful progress — especially around agents, world understanding, CodeMender, and SynthID. The next frontier is not only what AI can understand or generate, but what it is allowed to execute. As agentic systems move closer to AGI, safety cannot remain only at the model or output layer. It needs a non-bypassable execution boundary: authorization, context, sensitivity, human approval where required, auditability, and real-time governance before action is released. In EMM™ terms: Capability can scale fast. Governance must scale deeper. Execution must remain bounded. That is where responsible AGI becomes structurally possible.

Xcllent hope 2050 we will have npu kid ppu pico processing unit