AI is likely to automate a lot of white‑collar work and cause significant job losses, especially for early‑career workers, while political leaders are unlikely to provide robust safety nets like UBI or a jobs guarantee.
The AI industry currently lacks a clear path to profitability, is burning massive sums on data centers and infrastructure, and could face a damaging bubble or require government backstops if revenues never justify the spending.
Local communities and politicians are increasingly resistant to data center expansion because of energy, water, and cost impacts, and the overall future of AI is highly uncertain — it might bring real benefits like medical advances or result in overhyped promises and economic harm.
Calls for ethical technology are missing a crucial element that involves a radical revisioning of our ideas about reality.
The metacrisis we face involves technology outpacing our cognitive, moral, and spiritual capacities, intertwined with a lack of coherent cultural or scientific story to explain consciousness.
Appealing for value-driven technology is ineffective without a deeper understanding of the metaphysical foundations that shape our culture and values, such as the concept of consciousness as fundamental to reality.
Alan Turing's foundational paper on artificial intelligence is often overlooked in favor of its famous concepts like the Turing Test. It's filled with strange ideas and a deep human yearning for understanding machines.
The idea behind the Turing Test, where a computer tricks someone into thinking it's human, raises questions about what intelligence really is. Is being able to imitate intelligence the same as actually being intelligent?
Turing's paper includes surprising claims and combines brilliant insights with odd assertions. It reflects his complicated thoughts on machines and intelligence, showing a deeper human story that resonates today.
Self-attention treats all positions symmetrically, so permuting tokens just permutes outputs; because attention is permutation‑equivariant, Transformers need positional encodings to learn token order.
Commutativity is a deliberate design trade‑off: it enables parallelization and is perfect for unordered data like point clouds, sets, and graphs, but it destroys order information so you must use non‑commutative models or inject positions when order matters (language, time series).
Commutativity shows up across ML: global pooling gives useful invariance but loses location, gradient aggregation and distributed training rely on commutative sums, and floating‑point associativity issues can still cause small nondeterminism.
There is a new index for newsletters that want to find brands willing to advertise. It helps connect brands to various newsletters without taking a cut of the money.
YouTube is becoming a popular choice for TV viewers, turning into a go-to place for casual watching. This is threatening traditional streaming services as people prefer YouTube for light viewing.
NBC News is trying something new by offering a subscription that removes ads but doesn’t hide any content behind a paywall. This could change how media companies think about subscriptions.
Distributed inference is becoming easier with AI collectives, allowing small groups to work with large language models more efficiently and effectively.
Automation in scientific experimentation is advancing with large language models like Coscientist, showcasing the potential for LLMs to automate parts of the scientific process.
Chinese government's creation of a CCP-approved dataset for training large language models reflects the move towards LLMs aligned with politically correct ideologies, showcasing a unique approach to LLM training.
The yen has weakened due to external factors like the Houthi attack, impacting Japanese economy and inflation, and market anticipation of interest rate changes. The disappointing wage report for November dampened expectations for a rise in interest rates by the Bank of Japan, leading to a weaker yen.
An accurate model for predicting the yen's strength has a standard error of about 3.4 yen. A sizeable discrepancy between the model's forecast and the actual yen value could either indicate a correction back to expected levels or suggest a long-term trend change.
The growth in nominal wages in Japan has consistently fallen short of the 3% goal needed for sustained inflation. This has influenced market expectations regarding the Bank of Japan's monetary policy decisions and consequently impacted the yen's valuation.
Uber handles huge amounts of data by processing real-time information from drivers, riders, and restaurants. This helps them make quick decisions, like adjusting prices based on demand.
They use a mix of open-source tools like Apache Kafka for data streaming and Apache Flink for processing, which allow them to scale their operations smoothly as the business grows.
Uber values data consistency, high availability, and quick response times in their infrastructure. This means they need reliable systems that work well even when they're overloaded with data.
Load tests help you see how well your API works with normal users. They show how many users it can support without slowing down.
Stress tests push your API to its limits to find out what happens when it's overloaded. They help you prepare for crashes and see how fast it can recover.
Spike tests check how your API handles sudden increases in traffic. They are important for making sure your service can handle bursts, especially during promotions.
Demand for efficient and cost-effective inference solutions for large language models is escalating, leading to a shift away from reliance solely on Nvidia GPUs.
AMD GPUs offer a compelling alternative to Nvidia for LLM inference in 2024, particularly in terms of performance and efficiency, catering to the growing demand for diverse hardware options.
CPU-based solutions, like those from Neural Magic and Intel, are emerging as viable options for LLM inference, demonstrating advancements in performance, optimization, and affordability, especially for teams with limited GPU access.
DeepSeek v3 is a powerful and cost-effective AI model with a good balance between performance and price. It can compete with top models but might not always outperform them.
The model has a unique structure that allows it to run efficiently with fewer active parameters. However, this optimization can lead to challenges in performance across various tasks.
Reports suggest that while DeepSeek v3 is impressive in some areas, it still falls short in aspects like instruction following and output diversity compared to competitors.
In crypto, the best projects often create intense loyalty like cults, not just regular communities. People connect on a deeper emotional level, making them highly devoted followers.
Successful crypto projects usually have a strong leader who inspires and drives the movement. These leaders often embody the values of the brand and attract passionate supporters.
A sense of exclusivity and belonging is crucial for cult brands in crypto. Members feel united against an 'enemy,' and they love showing they are part of something special with symbols, language, and shared goals.
Big tech used to treat optimization as the core task, using data and engagement to constantly make products better. That era of relentless improvement has ended.
Platforms now tolerate degraded user experiences in pursuit of profit and dominance — a shift called enshittification — and high-profile moves like Elon’s changes at Twitter helped prove owners can cut quality without losing control.
The turn toward enshittification was driven by factors like runaway valuations, crypto and speculative hype, weakened regulation, and billionaire incentives; it probably won’t last forever and may end with a market or AI bubble collapse, but what comes next is uncertain.
Great companies focus on solving heartfelt problems to create successful and lasting businesses.
Identifying a heartfelt problem involves looking beyond surface-level solutions and understanding the emotional, functional, frequent, urgent, and unavoidable aspects of the problem.
To determine if a heartfelt problem is worth solving, conduct market research, speak with target customers, and focus on building relationships within the industry by understanding the core customer problem.
Hangzhou is becoming a tech hub in China with companies like DeepSeek and Unitree, but it has different strengths compared to Silicon Valley. Instead of having major venture capital and elite talent, it relies on local government support and a flexible approach to innovation.
While Hangzhou lacks the same level of university-industry connections and industrial history as Silicon Valley, it has created a unique environment where small companies can thrive without being overshadowed by big state-backed firms.
The success of Hangzhou's tech scene highlights how different regions can have their own paths to innovation, showing that there's not just one way to build a successful tech ecosystem.
Japan has a significant opportunity for economic growth through entrepreneurship and innovation, with potential for a tectonic shift in civil society.
Richard Katz's new book highlights the importance of Japan seizing the chance to revitalize its economy by generating innovative companies and above-par growth.
Key megatrends like generational shifts, technological advancements, and political stresses are identified as factors that could reshape Japan's economic future according to Katz.
Evil is a willful, unjustified attack that destroys another person’s freedom and rejects reason; it’s more than mere wrongdoing.
Evil differs from ordinary immorality or illegality because it repudiates the moral contract. An evildoer can be treated as unfit for society and legally incapacitated.
Philosophy and clear, objective standards help us detect and define evil. This lets societies respond through law and reason instead of emotional or arbitrary punishment.
Stop outdated controls like mandatory 90-day password changes and security questions and instead rely on password managers plus MFA.
Move away from checkbox trainings and dozens of point tools; security teams should build engineering solutions, use automated guardrails, and consolidate tooling to actually reduce risk.
Make security an enabling partner by aligning compliance to real risk, supporting safe AI adoption, delivering measurable ROI, and building trust through strong detection, response, and clear communication.
Google is working on a distributed training approach named DiPaCo to create large neural networks that break traditional AI policy focusing on centralized models.
Microsoft and OpenAI plan to build a $100 billion supercomputer for AI training, signaling the transition of AI industry towards capital intensive endeavors like oil extraction or heavy industry, touching on regulatory and industrial policy implications.
Sakana AI has developed 'Evolutionary Model Merge' method to create advanced AI models by combining existing ones through evolutionary techniques, potentially changing AI policy by challenging the need for costly model development.
The future of AI is not just about exciting advancements, but also about who gets to control the technology. Companies like OpenAI and Google currently hold a lot of power, but open-source models could change this.
Some AI models perform better than others, and we don't fully understand why. This difference in quality may come down to the talent behind the models, not just the data or hardware.
Instead of worrying about extreme scenarios, the impact of AI will likely be more mundane and integrated into everyday life, similar to how air conditioning changed industries without anyone really noticing at first.
Reverse engineering found the game records button presses into a hex "accumulator" and uses specific button sequences to unlock secret teams; the All Teams code listed on cheat sites also works on the US PlayStation version.
There’s a "Lewd lineup" Easter egg that appears when you unlock Secret/England 1966 vs Europe/Rep of Ireland and enter a second button code — it replaces the pre-match player lineup with an explicit (NSFW) image; that effect is absent in the PAL PlayStation release but does appear in the PC port.
A separate multi-part cheat triggers a voice saying "Oh, yeah!" and seems intended to enable extra sound effects, but the audio never plays during matches because the referenced sound file is missing; these findings came from inspecting memory and decompiling the game with tools like RALibretro and Ghidra.
Google found that psychological safety is crucial for an effective team, along with dependability, structure and clarity, meaningful work, and impact.
Team effectiveness is more about how team members collaborate rather than who is in the team.
Creating a culture of psychological safety where team members feel comfortable taking risks and expressing themselves without fear of repercussion can significantly boost team performance.
ADT confirmed a data breach where customer information was leaked online. They are investigating how deep the breach goes and are working on fixing their systems.
A major background check company had a huge data breach exposing nearly 3 billion records. This raises concerns for anyone who has had a background check done.
Microsoft revealed multiple serious vulnerabilities in their products. Users are advised to update their systems promptly to protect against potential attacks.
Multiple reports of harassment and misconduct by key figures in the esports industry were brought to light, leading to their termination.
New management at Evil Geniuses used past incidents involving employees as excuses to remove them, while also driving out senior employees who challenged their decisions.
The company culture at Evil Geniuses shifted dramatically after the departure of senior staff, leading to a challenging and unbearable work environment.
Agency can be wise or foolish: wise agency means experimenting and choosing a sustainable, genuine path, while foolish agency is doingwhatever it takes to get ends without regard for consequences.
People often move through phases — mastering career 'hoop-jumping' that masks insecure agency, then 'blowing up' their life — and the danger is trading one identity for another or making rejection your new personality.
To become more wisely agentic, surface and question your unconscious scripts by noticing which beliefs trigger strong reactions, and allow yourself to get lost and experiment instead of seeking quick belonging or monetizing uncertainty.
Efficiency improvements can be achieved in AI systems by varying the frequency at which GPUs operate, especially for tasks with different input and output lengths.
Governments like Canada are investing significantly in AI infrastructure and safety measures, reflecting the growing importance of AI in economic growth and policymaking.
Advancements in AI technologies are making it easier for individuals to run large language models locally on their own machines, leading to a more decentralized access to AI capabilities.
A long shortfall in residential construction since the mid-2000s has left roughly a 15 million‑home gap and driven net residential investment down from a sustainable ~2% of GDP to about 0.6%, creating a cumulative $7 trillion deficit.
That shortage has inflated land rents across many cities, acting as a regressive transfer from renters and new buyers to existing owners and raising nominal GDP and inflation without raising real GDP.
Building many more homes—especially rental and 'missing middle' units bought by investors—would replace land rents with structure rents, lower housing costs over time, and shift wealth away from landowners toward renters and new homeowners.
Natural-language theories fit inside one human brain and are therefore limited by our cognitive capacity, so they struggle to capture complex social systems and often give only vague answers.
The machine-learning 'bitter lesson' shows that scaling data and computation often beats hand-built symbolic theories, so social science should rethink the theory-first paradigm and embrace more data-driven, computational approaches.
Theory should be treated as code and engineered artifacts, and metascience must evaluate platforms, practices, and forecasting so science gains direct apertures to the world and can tell which theories actually work in practice.
A single clear sentence from a credible leader can reframe how someone sees themselves and send their career down a very different path.
Powerful mentorship is often short and works by naming undervalued strengths, offering a new identity, and granting permission to act rather than giving long advice.
Leaders should point out others’ potential because that recognition lowers barriers and compounds into bigger opportunities. People earlier in their careers should pay attention and act when a credible person reflects a new possibility for them.
Perception gives direct, non-inferential awareness of external objects when a perceptual experience assertively represents the world and that representation is roughly satisfied and non-accidentally caused by the object.
Perceptual experiences are internal states that have representational content, qualitative character, and a forceful feeling of presence; they are the vehicles that present the external world to us and are what differ in hallucinations or illusions.
Treating experiences as the objects of awareness rather than as the vehicles of awareness is a mistake that leads to indirect realism, skepticism, or idealism; correctly understood, experiences enable direct awareness of real external things.
Informal polls on Discord and LinkedIn had low response and are hard to interpret, but they did identify a small group of respondents who actually have purchasing influence.
Even though Roche's Axelios pricing isn't much better than Illumina's, the product still appears compelling to a subset of potential buyers.
Using rough assumptions about market size (>2000 instruments) and the poll results, a back‑of‑the‑envelope projection yields about 250 Axelios units in the first year, but that number relies on several optimistic assumptions and substantial uncertainty.
Many business owners think their business can't run without them due to fear of losing quality. But with the right systems, it can thrive even in their absence.
Bottlenecks come from controlling client communication and deliverables too tightly. Letting go and empowering others can free up time and improve efficiency.
Creating clear processes and hiring help allows business owners to focus on growth. Shifting to scalable models can also help in generating consistent income.
A weekly 10-minute series will analyze past investment decisions to help experienced investors improve their process quickly.
Each autopsy reviews the original thesis, lays out the facts of what happened, explains why it unfolded that way, and extracts practical and behavioral lessons.
Readers are encouraged to actively engage by pausing after the thesis, questioning assumptions and biases, and using the lessons to avoid mistakes or spot opportunities.