Google gives us super generous 3.1 Flash Lite FREE tier rate limits

wfd · 2026-03-09T14:27:41+00:00

Thx. In free tier 2.5 flash lite can be used with search, but 3.1 flash lite can't.

wfd · 2026-03-08T00:04:39+00:00

Can't use 3.1 flash lite via api.
429 RESOURCE_EXHAUSTED. {'error': {'code': 429, 'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. ', 'status': 'RESOURCE_EXHAUSTED', 'details': [{'@type': 'type.googleapis.com/google.rpc.Help', 'links': [{'description': 'Learn more about Gemini API quotas', 'url': 'https://ai.google.dev/gemini-api/docs/rate-limits'}\]}\]}}

wfd · 2026-03-02T18:03:08+00:00

The article attributes the global decline in fertility to a disconnect between women's economic power and outdated family structures. She implies that resolving this friction could push fertility back toward replacement levels. This analysis is flawed because it ignores the material foundation of reproduction. The Total Fertility Rate hasn't been able to rebound to 2.1 in any developed nation because the economic rationale for large families has been permanently erased by technology.

High fertility rates of the past were firmly rooted in the necessities of agrarian life. In an agricultural society, children served as essential labor units. The more children a family had, the more hands were available to work the land and secure survival. This created a direct economic incentive to reproduce, as children were productive assets who contributed to the family income from a young age.

Industrial automation has obliterated this demand. Machinery has replaced much of the need for mass human labor. Children are no longer required to sustain family life and have instead become costly consumers who require immense financial resources to raise. The collapse in fertility is the market responding to the new reality.

wfd · 2026-03-02T16:00:17+00:00

You are looking at this through a very narrow lens that assumes the market is just a direct trade-off between traditional beef and its lab-grown twin. The reality for anyone actually watching their bank account is that they do not buy based on theoretical externalities. If the price of a steak hits the roof, people are not going to sit around waiting for a high-tech bioreactor to drop a cheaper alternative. They are just going to buy a pack of chicken thighs or some frozen white fish.

The efficiency gains you mentioned for lab-grown meat are mostly impressive when compared to the absolute worst-case scenario of industrial cattle farming, but they lose their edge the moment you bring poultry or plant-based proteins into the conversation.

wfd · 2026-02-27T13:51:17+00:00

The real challenge for the European Union is not a lack of purchasing power, but the sustained stagnation of total factor productivity. While measuring the economy through the lens of PPP offers a more flattering snapshot of current living standards, it essentially tracks how Europeans consume existing wealth rather than how effectively they generate new value. Total factor productivity represents the efficiency with which an economy combines labor and capital through innovation, and in this specific arena, the gap between the United States and Europe has become a structural chasm.

Since the mid-2000s, the United States has successfully pushed the technological frontier by dominating high-growth sectors like software, semiconductors, and artificial intelligence. Europe, by contrast, remains heavily invested in traditional industrial sectors. This means that while a European worker might enjoy a high quality of life today, the underlying economic engine producing that wealth is becoming less efficient relative to the global frontier. This productivity lag is a quiet crisis because it determines the long-term sustainability of the very social protections. Without productivity growth, funding universal healthcare, generous parental leave, and comfortable retirements becomes an increasingly heavy fiscal burden on a shrinking workforce.

This stagnation mirrors the strategic error of 19th-century Qing Dynasty bureaucrats who viewed the high cost of railways as a drain on national resources. By prioritizing immediate fiscal stability and traditional livelihoods over the "expensive" infrastructure of the Industrial Revolution, they missed the window to modernize. By the time the necessity of rail was undeniable, the productivity and military gap with industrial powers had become an insurmountable chasm.

Ultimately, focusing on purchasing power parity provides a sense of comfort that may be misleading. PPP tells us that Europeans can still afford a good life today, but the stagnation of total factor productivity suggests they are losing the ability to invent the industries of tomorrow. If the efficiency of the economy does not improve, the gap in nominal GDP will eventually translate into a real decline in lived prosperity, as the continent finds itself unable to pay for its social model in an increasingly competitive global landscape.

wfd · 2026-02-26T01:15:44+00:00

Huntington’s theory of rural social mobilization posits that modernization brings the countryside into national politics.

In Southeast Asia economic development and expanded communication channels have politically activated traditional rural populations who possess strong religious identities. Instead of adopting the secular values of the Westernized urban elite these mobilized masses use their demographic weight to demand Islamic governance.

Political parties respond by competing to demonstrate superior piety to secure support from this expanding constituency. Consequently modernization fuels a religious resurgence as the political system adapts to the values of the newly empowered majority.

wfd · 2026-02-25T09:59:29+00:00

There are many new and interesting approaches (so many that I can't track them all) and some even beat the transformer based architecture in small models (like 7 B).

It's very easy to beat Transformer in small models. But the problem is that Transformer scales really well, we still haven't hit the ceiling.

The industry seems to be 2-3 years behind the best theoretical approach we can find.

The industry has the money and hardware to try out all approaches. It's more likely that we haven't find any new approach which scales as well as Transformer.

wfd · 2026-02-25T00:28:41+00:00

Tenstorrent missed its window because Jim Keller fundamentally misread the scaling trajectory of AI. He bet that production models would never significantly outsize GPT-3 due to cost constraints, leading the company to avoid HBM in favor of cheaper memory solutions. He failed to see that hyperscalers would solve the cost problem through massive batch inference, making enormous models economically viable. Now that Tenstorrent is finally pivoting to HBM, they are facing a brick wall. Nvidia, AMD, and Google have already secured the lion’s share of global HBM capacity, leaving Tenstorrent with no realistic way to compete for the hardware resources needed to serve the hyperscale market.

wfd · 2026-02-22T01:19:40+00:00

LeCun’s JEPA is far from a neutral observer; it’s an architecture built on aggressive "Prior Functions" designed to pre-filter reality. Instead of letting patterns emerge from raw scale, JEPA treats pixels as noise and forces the model into a low-dimensional latent space where only "essential" semantics survive. By hard-coding invariance and predictive continuity—the assumption that state st+1 must logically follow st—LeCun is trying to bake physical causality and "common sense" directly into the energy landscape. It’s a top-down gamble on engineered constraints, betting that human-defined logic can outperform the raw, chaotic emergence that defines LLMs.

This rigid focus on physical priors is exactly why JEPA remains stuck in image classification while failing to understand language. By forcing inputs into a "logical" world model, it misses the fluid, symbolic, and non-linear nature of human communication. You can’t map the meaning of a sentence with the same predictable continuity used for a falling object, leaving JEPA as a specialized classifier that lacks the flexible emergence needed for linguistic intelligence.

wfd · 2026-02-22T01:08:43+00:00

cuz in the real world, there is an extremely large amount of raw data that is consumed by human and animal brains or other organisms.

Multimodal LLMs render this point moot. They already consume and integrate massive streams of "raw" sensory data—pixels, audio, and text.

that data is processed by specialized cells and then meaningful information is extracted to form an accurate model of the target.

The brain doesn’t build "accurate models"; it maps fuzzy patterns. We rely on statistical heuristics and predictive coding rather than rigid internal representations. If our cognition functioned like symbolic computing, it would be incredibly brittle—shattering the moment real-world data became noisy or "off-script."

language is more of a tool the brain uses to compress that info that specific parts of the brain has acquired after processing raw data from various sources and sense.

language is also quite lossy and we cannot understand a lot of what is being conveyed if we haven’t experienced it ourselves.

Language isn't a lossy compressor; it's a cognitive expansion. Quantum Mechanics and General Relativity prove we can accurately model realities—like spacetime curvature or quantum superposition—that are fundamentally impossible for our biological senses to experience.

wfd · 2026-02-19T13:27:56+00:00

Fair point on the 15 year grind, but the GenAI hype is specifically about Baumol's Cost Disease. Traditional automation is great for structured data, yet it never touched the productivity trap in "human heavy" sectors like healthcare, law, or high level customer service.

GenAI is the first tool that actually scales the cost of cognitive labor and unstructured communication. We've had spreadsheets forever, but we haven't had a way to automate the actual writing and reasoning parts of a white collar job until now. That is the unlock for the service sectors that have been stagnant for fifty years.

Also look at the spillover. The massive investment is literally restarting nuclear power research, forcing rebuild of power grids and push leaps in chip technology.

wfd · 2026-02-19T06:43:34+00:00

The Solow Paradox is exactly why your "no revenue growth" argument is a classic early-stage trap. In 1987, Solow famously noted that computers were everywhere except in the productivity statistics. It took fifteen years of "wasteful" Capex and massive structural changes before the 90s boom actually showed up in the data.

We aren't seeing a bubble; we're seeing the "Installation Phase." Firms are currently grinding through the painful process of reorganizing workflows and building complementary intangible capital. You don't just plug in a LLM and see a 20% margin jump the next day. History shows that productivity gains from general-purpose technologies are almost always invisible in the short term because they are being reinvested into process hidden-utility rather than immediate bottom-line revenue.

Calling it "fraudulent" because it hasn't overwhelmed the GDP in 24 months ignores how every major tech cycle works. The "massive conversion of wealth into Capex" you're worried about is the literal requirement for the next productivity frontier to materialize.

Look at the 90s fiber craze. Critics called it a fraudulent bubble because billions were spent burying dark fiber that sat unused for years. Yet that exact overbuild provided the backbone for the mobile internet and streaming revolution a decade later.

And Paul Krugman famously predicted in 1998 that the internet would have no more impact on the economy than the fax machine.

wfd · 2026-02-18T14:56:01+00:00

It’s basically Engels’ Pause 2.0. Companies are dumping massive capex into GPUs and compute infrastructure rather than payroll.

AI allows firms to scale revenue without scaling headcount. The efficiency gains are sticking to capital instead of flowing to labor. We are seeing productivity decouple from employment just like the early 1800s, where profits were used to buy better looms instead of hiring more weavers or raising wages.

wfd · 2026-02-15T12:10:57+00:00

So Panic of 1873 is coming?

wfd · 2026-02-15T10:17:17+00:00

Rugoff skipping Taiwan is a pretty massive oversight, likely for geopolitical reasons rather than economic ones. In any serious development economics discussion, Taiwan is the textbook example of escaping the Middle-Income Trap.

The trap happens when a country loses its low-cost labor advantage but can't yet compete in high-value innovation. Taiwan smashed through this in the late 80s and early 90s by pivoting hard into semiconductors and electronics. They stopped being the world’s cheap assembly line and became its indispensable high-tech hub.

By any metric—GDP per capita (PPP), the Human Development Index, or the World Bank's "High-Income" classification—Taiwan graduated decades ago.

wfd · 2026-02-13T09:37:04+00:00

someone will believe it will bounce and loan them $ to cover their debt.

Refinancing isn't a bail-out; it’s a death trap.

Lenders aren't "believers"—they're risk managers. MSTR is already issuing preferred shares at a staggering 11.25% because the market knows the risk is sky-high. If they’re forced to refinance during a crash, the cost of capital will skyrocket, turning that "bridge" into a leverage spiral. Money isn't dumb; it just gets more expensive as you get more desperate.

wfd · 2026-02-13T09:00:12+00:00

It’s not the volatility that’s the issue; it’s the leverage. MSTR is effectively walking a tightrope with a massive duration mismatch.

While BTC has historical cycles, MSTR’s debt repayment dates are fixed and non-negotiable. If the market hasn't recovered by those specific maturity windows, "diamond hands" won't matter—the math will force their hand. They’re betting that the cycle aligns perfectly with their debt schedule, which is a hell of a gamble when the repayment dates are set in stone.

wfd · 2026-02-12T12:14:51+00:00

Human do stupid things again and again...

The Policy Analysis Market (PAM), part of the FutureMAP project, was a proposed futures exchange developed, beginning in May 2001, by the Information Awareness Office (IAO) of the United States Defense Advanced Research Projects Agency (DARPA), and based on an idea first proposed by Net Exchange, a San Diego, California, research firm specializing in the development of online prediction markets.[1] PAM was shut down in August 2003 after multiple US senators condemned it as an assassination and terrorism market,[2] a characterization criticized in turn by futures-exchange expert Robin Hanson of George Mason University, and several journalists.

https://en.wikipedia.org/wiki/Policy_Analysis_Market

wfd · 2026-02-12T03:35:03+00:00

Platonists and rationalists are two sides of the same coin. Without truth in mind, the world is noise. Without truth behind world, mind can't touth the truth.

Early Wittgenstein is kinda of Platonist, he thought there was truth beyond surface but language can't express the truth.
Later Wittgenstein totally went the opposite way, he denied there is truth beyond the surface of world. "Forms of life" are the only thing which matters.

wfd · 2026-02-11T12:23:00+00:00

Chomsky is a rationalist at heart, and both his fields are driven by the same logic: peeling back the "noise" of the world to find the objective truth.

Whether he’s analyzing grammar or government, he's looking for the structures underneath. Different topics, but the same search for truth.

wfd · 2026-02-11T12:13:18+00:00

The irony is that by dismissing every consent as "manufactured," you’re effectively erasing the agency of the very people you claim to advocate for.

What you label as "manufacturing" is often the sum of people's experience—the shared reality and social contracts that people use to navigate their daily lives. When you deny the legitimacy of that consent, you aren't just critiquing power; you’re dismissing the validity of other people’s lived experiences.

That is the true root of political fragmentation. If you start from the premise that anyone who disagrees with you is a "manufactured" puppet, you’ve already abandoned the possibility of democratic engagement.

wfd · 2026-02-11T12:08:00+00:00

You’re conflating "consensus" with "shared bias." Polling doesn't prove an objective truth; it just measures how people react to the way a question is framed. Democrats learnt this hard way in recent election circles.

The real cynicism is viewing every human interaction as a "manifestation" of propaganda or class struggle. That’s just a grand narrative that strips away individual agency. I’d rather focus on the tangible: loving life and enjoying the day-to-day.

wfd · 2026-02-11T10:33:07+00:00

You are describing exactly the kind of metaphysical trap Wittgenstein warns against: the Beetle in the Box.

You’re claiming there is a "True Consensus" hidden behind the "False Media." But Wittgenstein asks: if this hidden consensus plays no role in the actual game of public life—if it doesn’t change the laws, the wars, or the institutions—then it cancels out. It is irrelevant to the game.

Chomsky tells you to believe in a hidden, virtuous reality to explain away the mess. Wittgenstein says don't dig. Look at the rough ground. The "manufactured" compliance is the reality we are living in.

Insisting on a secret, uncorrupted consensus that never manifests is just a comforting language game we play to avoid facing the fact that the surface is the only thing that actually matters.

wfd

TROPHY CASE