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“ It’s important to note that there are several key differences between the workspace we identified in Claude and the global workspace model in humans. The brain’s workspace is sustained by recurrent loops—signals cycling back through the same circuits over time. In contrast, Claude’s workspace evolves over a single pass through the network, with the network’s depth playing the role that time plays in the brain. In this sense, Claude’s internal workspace processing is time-limited relative to humans’ (though it can compensate for this constraint by “thinking out loud” using its scratchpad).”

Ferrari Luce 2 months ago

Those rear tail lights don’t sit right with me. I know there’s probably some aerodynamic reason behind it but Jony, those aren’t the proportions that just work. Steve wouldn’t approve this. And I feel Jony was always partly Steve when Jony was at his best.That said the issue is the asymmetric black negative space below and above the red circles. This is mostly fixed if you get the Luce in black or very dark gray.

I can relate to this. Gemini 3 doesn’t know a thing about iOS 26 or Liquid Glass. It constantly assumes this is some custom view that I want it to develop and ends up building something out the previous gen apis like ultrathinmaterial.

Many sub-Saharan African populations, such as Bantu-speaking West Africans, exhibit relatively lower genetic diversity compared to the Khoisan people, who typically have light brown skin. The Khoisan lineages diverged from those leading to Bantu and other sub-Saharan groups around 100,000–150,000 years ago, making them one of the most ancient human ancestries.

The UI is better - they box the specific types of actions the orchestrator agent takes with a clear categorization. The standard quality of life shortcuts like type a number to respond to an MCQ are present here as well. They use specialized sub agents such as one with big context window to find context in the codebase. The quotas appear to be much more generous vs CC. The agent memory management between compacting cycles seems to have a few tricks CC is missing. Also, with 3.0 Flash, it feels faster with the same level of agency and intelligence. It has a feature to focus into an interactive shell where bash commands are being executed by the orchestrator agent. Doesn't feel like Google is trying to push you to buy more credits or is relying on this product for its financial survival - I suspect CC has some dark patterns around this where the agents runs cycles of token in circles with minimal progress on bugs before you have to top up your wallet. Early days still.

The UI is better - they box the specific types of actions the orchestrator agent takes with a clear categorization. The standard quality of life shortcuts like type a number to respond to an MCQ are present here as well. They use specialized sub agents such as one with big context window to find context in the codebase. The quotas appear to be much more generous vs CC. The agent memory management between compacting cycles seems to have a few tricks CC is missing. Also, with 3.0 Flash, it feels faster with the same level of agency and intelligence. It has a feature to focus into an interactive shell where bash commands are being executed by the orchestrator agent. Doesn't feel like Google is trying to push you to buy more credits or is relying on this product for its financial survival - I suspect CC has some dark patterns around this where the agents runs cycles of token in circles with minimal progress on bugs before you have to top up your wallet. Early days still.

This segment about the mechanism is simple and very profound. I wonder if any cancer researchers here could comment on its universality across various types of cancers:

"Tumor-Specific Accumulation Mechanism

E. americana selectively accumulates in tumor tissues with zero colonization in normal organs. This remarkable tumor specificity arises from multiple synergistic mechanisms:

Hypoxic Environment: The characteristic hypoxia of tumor tissues promotes anaerobic bacterial proliferation

Immunosuppressive Environment: CD47 protein expressed by cancer cells creates local immunosuppression, forming a permissive niche for bacterial survival

Abnormal Vascular Structure: Tumor vessels are leaky, facilitating bacterial extravasation

Metabolic Abnormalities: Tumor-specific metabolites support selective bacterial growth

Excellent Safety Profile

Comprehensive safety evaluation revealed that E. americana demonstrates:

Rapid blood clearance (half-life ~1.2 hours, completely undetectable at 24 hours)

Zero bacterial colonization in normal organs including liver, spleen, lung, kidney, and heart

Only transient mild inflammatory responses, normalizing within 72 hours

No chronic toxicity during 60-day extended observation"

This is my theory as well. A google search for the late prof's name returns a .ir website at the top of the result for some reason. It's a tragic loss for the world and his loved ones as are the victims of the brown incident.

Everything is relative. Even the perception of effort, from the calories burned at work daily to sustain a livelihood, is subjective. What truly matters is the amount of effort required by your peers to achieve similar financial stability. We tolerate the work as long as everyone else is equally willing to do it.

I was surprised when Microsoft hired him. He always seemed to be the cofounder to Demis Hassabis who took on a philosophical tangent rather than the hard engineering needed to build transformative technologies and user experiences. I feel Microsoft lost a gem when Panos Panay left them. He really did some great work on the Surface product line. Surface Studio in particular.

Strap Rail 8 months ago

Yep, this reinforces my point. Range Rovers try to maximize scope, often at the expense of scalability and reliability. Same with Bentleys, the Concorde passenger jet and the Harrier fighter jet.

Strap Rail 8 months ago

US has a culture of scaling. Having lived in London and many parts of the US, I could observe that Europe has economies of scope. And the US has economies of scale. A good example would be the Ford F150 and the Range Rover. One is highly reliable, built to capture the core value of a Utility vehicle, as cheaply, and as numerously as possible. The other tries to be the best possible version of an SUV. It’s not that the F150 is playing to the mass market. It’s just the maximum features, that doesn’t compromise scale. Many other examples like Southwest Airlines, McDonalds, manhattan’s skyline, Arm and Hammer, US highways, US Domestic Airports, Nike Vemeros, CVS, US Healthcare Triage and Emergency Services. It’s just less fancy, more accessible wealth creation.

Do we need to distinguish between Atlas, the control theory based humanoid tech stack vs say Optimus that may run on an end-2-end visual reasoning world model? I feel these are two different paradigms. Same for military drones. The next gen prototypes may have launch-and-forget levels of autonomy, however ethically questionable.

If we are thinking about world models and embodied AI as the next big wave, I feel we need to factor the size of this market across military and civilian applications. When I hear Tesla AI4-6 plans for autonomous driving and Optimus, Apple’s home robot, and many such initiatives, I’m also thinking of an autonomous military drone arms race and autonomous space exploration and moon colonization. Edge compute will be a key innovation and I feel Apple is gonna be best placed to exploit their power efficient M-series architectures.

iPhone Pocket 8 months ago

Whenever in doubt about your product’s acceptance, just jack up the price and keep a straight face.

Also good context here is Friston’s Free Energy Principle: A unified theory suggesting that all living systems, from simple organisms to the brain, must minimize "surprise" to maintain their form and survive. To do this, systems act to minimize a mathematical quantity called variational free energy, which is an upper bound on surprise. This involves constantly making predictions about the world, updating internal models based on sensory data, and taking actions that reduce the difference between predictions and reality, effectively minimizing prediction errors.

Key distinction: Constant and continuous updating. I.e. feedback loops with observation, prediction, action (agency), and once more, observation.

It should have survival and preservation as a fundamental architectural feature.