u/4billionyearson

Two radial charts comparing monthly UK temperature and sunshine anomalies in 2026 against a 1961-1990 baseline, with 2025 (the UK's hottest and sunniest year on record) shown as the white reference ring on both.

2026 so far (Jan-Jun) is the UK's hottest first half of a year on record, and its temperature line sits close to or outside the 2025 ring on most months. But on the sunshine chart, 2026 sits well inside the 2025 ring every month, meaning consistently less sunshine.

The temperature story is largely driven by January and February, which are driving most of the gap versus 2025 rather than June's record breaking heatwave, which is a distinct effect worth separating out.

Likely candidates include cloud cover and humidity suppressing overnight cooling (raising minimums even on lower sunshine days).

Note: the legend includes additional reference lines (1900-2026 range, 2016-2025 average) that are hidden in this static export for visual clarity. They are visible and toggleable on the live interactive version linked below ...

https://4billionyearson.org/climate/helix?region=uk#climate-spiral

NOAA's dynamical model plume has the new El Nino peaking at +2.6°C/+4.7°F in Sep-Nov 2026. These models are short term (9 months or so) as errors compound further out.

A longer range well regarded CNN model (Seoul National University ACE Lab), has just issued a 24 month run that shows the full cycle for the first time ... a higher, later peak around +3.2°C/+5.8°F in early 2027, declining into a weak La Niña by late 2028.

Does this affect climate change?

Each major El Nino since the 1970's has left a higher temperature floor behind, a 'ratchet' effect. This one's projected to add +0.16°C/+0.29°F to global warming

Source/chart ... 4billionyearson.org/climate/enso#forecast

Temperature Ratchet ... 4billionyearson.org/climate/symphony

Iceland's May was the warmest in 86 years ... +5.15°C/+9.3°F above the 1961-1990 baseline, 4x the global rate.

Iceland also had its hottest Spring on record ... 2.5°C/36.5°F

The North Atlantic Oscillation was negative in May ... -0.74

The Pacific-North American pattern was negative ... -1.27

NAO & PNA normally suppress warmth in the North Atlantic, so Iceland's spring records seem very out of place?

Might this be an early indicator that Iceland is somehow shifting into the same amplification rate as the high Arctic (which warms about 4x faster than the global average)?

Probably not, as Iceland's longer term rate is lower, at 2.4x ?

This seems more than normal variation, but I cannot see what could be driving it?

More detailed numbers and sourcing here if anyone wants to dig into it: https://4billionyearson.org/posts/warmest-spring-in-86-years-negative-nao-what-s-going-on-in-iceland

I've been digging into the energy efficiency gap between biological and artificial neural systems and the numbers are wilder than I expected.

The human brain handles perception, memory, language, motor control, emotional regulation, and creative thought on roughly 12-20 watts. About the same as a bedside lamp. Switzerland's Blue Brain Project estimated that simulating the brain's full processing in real time would require approximately 2.7 billion watts, comparable to three nuclear power stations.

A few things that explain the gap, beyond the obvious "biology is efficient":

No von Neumann bottleneck. In a conventional computer, memory and processing are physically separate, so data is constantly shuttling back and forth, burning energy at every step. Synapses in the brain both store information and compute with it. There's no equivalent shuttle.

Sparse activation. Most neurons are quiet at any given moment. Power draw scales with what the brain is actually doing, not its theoretical max. AI hardware tends to keep huge numbers of transistors switching regardless of whether the operation is immediately needed (though mixture-of-experts architectures are a move toward fixing this).

Event-driven signalling. Neurons fire spikes and sit at rest otherwise. Digital transistors switch on/off billions of times a second, consuming power on every transition regardless of whether it's useful.

A peer-reviewed estimate in Frontiers in Neuroscience puts the brain's energy efficiency advantage over silicon at roughly 2.7 × 10¹³, accounting for both per-operation efficiency and the fact that current hardware takes about 30,000x longer than real time to simulate biological activity.

The interesting part isn't just "brains good, chips bad" though. There's serious neuromorphic computing research trying to close this gap:

• TDK/CEA have a working spin-memristor (uses quantum magnetic properties to act as memory and processor simultaneously, like a synapse), targeting under 1/100th of current AI power draw
• University at Buffalo is working with phase-change materials to replicate the brain's rhythmic electrical oscillations
• Texas A&M's "Super-Turing AI" uses Hebbian learning ("cells that fire together, wire together") instead of backpropagation, and tested it on a drone that navigated a novel environment without prior training, faster and less energy-intensive than conventional AI

Efficiency gains historically get eaten by the rebound effect. If neuromorphic chips cut cost per query by 100x but usage grows 200x, total consumption still rises. The IEA has already revised its AI energy projections upward twice.

I wrote this up with full sourcing here if you want the deeper dive: https://4billionyearson.org/posts/the-staggering-inefficiency-of-ai-v-the-human-brain

Curious what people here think about whether brain-inspired architecture is a genuine path forward or whether it just hits different bottlenecks once you scale it.

A conventional temperature time series shows the trend clearly enough, but it flattens out the seasonal cycle. Every year looks roughly the same shape, just shifted upward. I wanted a form that kept the seasonality visible while also showing the long-run trend. A helix does both, each year is a full loop, and the drift outward and upward over seven decades is immediately readable without needing to interpret an axis.

The Paris Agreement thresholds (+1.5°C and +2°C above the 1850–1900 pre-industrial baseline) appear as reference rings in the floor plane, so you can see how individual years relate to those boundaries spatially rather than just numerically. 2024, the warmest year on record, sits at the outer edge of the +1.5°C ring.

A few things it shows that a line chart doesn't:

• The seasonal rhythm of each year is preserved, you can see which months are pulling each year's loop outward
• The clustering of recent years near the Paris rings is visceral in a way that a trend line isn't
• The coldest year (1964, shown in blue) and the 2016–2025 mean give you immediate visual anchors for how much has shifted

It's not just global either, you can switch to any country, US state, or UK region and the helix rebuilds for that location's data.

Data is NOAA Global Land+Ocean. You can also switch to anomaly view, toggle Land-only, and there's a live sidebar with CO2, sea level, sea ice, and ENSO.

🔗 https://4billionyearson.org/climate/helix

Interested in any feedback on the form itself, whether the 3D projection helps or hinders legibility, and whether the Paris rings are helpful.

After struggling to find a good single source of weather/climate data for where I live (south coast), in comparison to the UK/World, I started downloading data and putting charts together ... I got slightly obsessed and ended up building a few visualisations and a whole website.

I found a few interesting things ...

• The strongest warming isn't in summer ... it's February.
• I was pretty sure it doesn't snow as much as it used to ... there are around 5 fewer frost days per year than when records began.
• I was sure that Spring arrives earlier now ... It does, 13 days earlier, but Autumn also arrives about 13 days later, making the whole 'warm period' 27 days longer overall.

This page contains all the above visualisations if anyone wants to explore the data: https://4billionyearson.org/climate/uk

The variation across the UK is much bigger than I expected ... as of May, the south has experienced both the hottest May and Mar-May period on record! North Scotland on the other hand, had one of its dullest May's ever.

You can look at the 12 UK regions here .. https://4billionyearson.org/climate#uk-regions

This chart compares season timing across three Köppen climate zones, using each region's first 30 years of records as a baseline vs the most recent 10 years.

The dashed outline shows the baseline growing season window. The solid bar shows the recent average. The dots represent individual years, with the dot colour showing the annual global temperature anomaly vs the 1901–2000 NOAA average.

Full interactive version (Global level) ... https://4billionyearson.org/climate/shifting-seasons

View for individual country, US state, or UK region ... https://4billionyearson.org/climate (scroll down once on the monthly update page)

Interactive version with full driver tooltips: https://4billionyearson.org/climate/symphony#timeline

Every year of global temperatures since 1950 plotted as a climate helix

Each loop represents one year of monthly global temperature anomalies relative to the 1961–1990 baseline.

Months run clockwise around the circle. Distance from the center shows how far temperatures deviated from the historical average.

Over time, the helix rises and expands outward as global temperatures increasingly cluster above historical norms.

Blue solid = coldest year
Blue dashed = 1961-1990 baseline

White solid = warmest year
White dashed = 2016-2026 mean

Red = individual years
Orange = 2026 so far

The dashed rings mark the Paris Agreement warming thresholds (+1.5°C and +2°C)

Data: Berkeley Earth / NOAA

Interactive version + animation:
https://4billionyearson.org/climate/helix

We've been waiting for the wrong thing.

For decades the dominant story has been the Singularity: one god-like superintelligence bootstrapping itself to incomprehensible power, at which point humans become irrelevant. It's a compelling story. According to a paper from Google's Paradigms of Intelligence team, published in Science, it's also almost certainly the wrong frame.

The argument: every major intelligence explosion in history has been social, not individual. Primate intelligence scaled with group size, not habitat difficulty. Language created what Tomasello calls the "cultural ratchet" - knowledge accumulating across generations without any individual rebuilding it from scratch. Writing and institutions externalised collective intelligence into systems that outlasted any single participant.

AI is likely the next step in that sequence, not a break from it.

What makes this genuinely surprising is the evidence from inside the models themselves. Reasoning models like DeepSeek-R1 don't improve by "thinking longer." They spontaneously generate internal multi-agent debates, distinct cognitive perspectives that argue, question, verify, and reconcile. Nobody trained them to do this. It emerged purely from optimisation pressure rewarding accuracy.

Intelligence, it turns out, defaults to social even inside a single mind.

If that's right, the path to more powerful AI doesn't run through building a bigger oracle. It runs through building richer social systems, and governing them the way we govern cities and institutions, not with a kill switch.

I wrote this up as a learning piece - not as an expert. Am genuinely curious what people here think. Is the singularity frame actually dead? And if intelligence is inherently social, what does that mean for alignment?

Full piece: https://www.4billionyearson.org/posts/forget-the-singularity-google-s-new-research-says-the-future-of-ai-is-a-social-explosion