COLOR ME OLO

Dick Pountain /Idealog 371/ 10 Jun 2025 12:15

I’ve expressed my feelings about science fiction before many, many, probably too many, times in this column. A big fan in my 1960s teens, a bout of illness in the ‘70s let me binge all the greats – Vonnegut, Ballard, LeGuin, Dick, Pohl, Bester etc – overdosing so badly that I never wanted to read sci-fi again. Looking back now as emotionally-retarded pseudo-intellectual sci-fi fans appear to be taking over the world, I think perhaps my immune system was telling me something. However this allergic reaction doesn’t apply to the closely related genre of fantasy (or gothic, or cosmic) horror. I still can cringe a little to M.P. Shiel’s ‘The Purple Cloud’, William Hope Hodgson’s ‘The House on the Borderland’, or the entire oeuvre of H.P, Lovecraft. 

One of Lovecraft’s stories, ‘The Colour Out Of Space’, struck me particularly hard. A meteorite lands in a tiny community in the New England woods, containing globules of a weird colour that isn’t in the solar spectrum: it has unpleasant effects that consume all living animals, plants and humans and turn them into grey ash. Several unsuccessful attempts have been made to film this story, hard work given that it’s not in the technicolor spectrum either: perhaps the nearest anyone has come is Alex Garland’s 2018  ‘Annihilation’ which clearly shows Lovecraftian influence and employs a digitally-produced shimmer in place of a new colour. I suppose Lovecraft’s story is a sort of parable about environmental destruction, but that’s not what explains its hold on me – I’ve always been fascinated by colour, studying its chemistry, reading up on all the various systems, appreciating great paintings and creating my own digital art as a favourite hobby.   

All of which explains my enormous excitement on reading in the Science Adviser newsletter about new research at the University of California Berkeley, which ‘creates’ a new colour that lies outside the gamut humans can perceive, but can be seen by shining a laser onto ones’ retina (don’t try this at home kids). First some background is required. You already know that our eyes, and hence also digital display devices, perceive or present colours as mixtures of the three components red (R), green (G) and blue (B). That’s because the retinas of our eyes contain three types of colour-sensitive cell called ‘cones’, sensitive to different wavelengths: long (L), medium (M) and short (S). Objects illuminated by natural sunlight stimulate L, M and S cones to different extents which gives us the experience of different colours. Red light primarily stimulates L cones and blue light S cones, but since M cones respond to the middle of the range, overlapping with both L and S, there’s no component of sunlight that stimulates M alone. 

The authors of the Berkeley paper (https://www.science.org/doi/10.1126/sciadv.adu1052) set out to investigate a new system for describing colour perception, by using a laser to illuminate retinal cells one at a time: 

“We introduce a principle, Oz, for displaying color imagery: directly controlling the human eye’s photoreceptor activity via cell-by-cell light delivery. Theoretically, novel colors are possible through bypassing the constraints set by the cone spectral sensitivities and activating M cone cells exclusively. In practice, we confirm a partial expansion of colorspace toward that theoretical ideal. Attempting to activate M cones exclusively is shown to elicit a color beyond the natural human gamut.”

Calling their new system Oz was of course a trigger for me, having cut my journalistic teeth on that notorious hippie journal where my articles were printed in every colour of the rainbow on a background of every other colour of the rainbow. But I digress. Their new colour, from stimulating M cells alone with a laser, they named ‘olo’. It can’t be reproduced in paint, ink or screen, so you’ll only ever see it sitting in a dentists’ chair with a laser strapped to your head: 

“Subjects report that olo in our prototype system appears blue-green of unprecedented saturation, when viewed relative to a neutral gray background. Subjects find that they must desaturate olo by adding white light before they can achieve a color match with the closest monochromatic light.”

Thankfully olo has not so far shown any inclination to suck the life force out of living beings and reduce them to grey ash. The best approximation is a light turquoise, a colour you might glimpse fleetingly when watching a big wave break on a rocky headland in bright sunshine. Astronomers for a while believed the whole universe, by mixing all the light together, would be a light turquoise but that turned out to be a bug in their software, and it’s now ‘cosmic latte’, a light beige (hex triplet value in standard sRGB #FFF8E7). 

[Dick Pountain wonders whether Olo could become ‘the new Pistachio’]

GOING NEURO

Dick Pountain /Idealog 370/ 05 May 2025 01:31

I’ve written many, many sceptical words about AI in this column over the years, railing against overconfidence and hype, hubristic pursuit of AGI, deepfakery and content pillage, but nevertheless I do believe AI – once we’ve civilised it – is going to be hugely  important to science, economics, robotics, control systems, transport and everyday life itself. Given the political will, public concern about misinformation, invasion of privacy, and theft of artistic data can be regulated away, but there would remain one colossal stumbling block, namely energy consumption. 

When AI corporations consider purchasing mothballed nuclear reactors to power their compute-servers the absurdity of AI’s current direction ought to be visible to everyone. The current generation of GPT-based AI systems depend on supercomputers that can execute quintillions of simple tensor arithmetic operations per second to compare and combine multiple layers of vast matrices holding encoded parameters. Currently all this grunt is supplied using the same CMOS semiconductor process technologies that gave us the personal computer, the smartphone and especially the computer game – the Nvidia chips that drive most AI servers are descendants of ones originally developed for rendering real-time 3D games. The latest state-of-the-art GPUs have a watts/cm² power density around the same as an electric cooking hob, and the power consumption of AI server farms scales exponentially, as the square of the number employed (order O(N²) in the jargon of complexity theory). 

In their 1978 bible of the CMOS revolution ‘Introduction to VLSI Systems’, Mead and Conway devoted a final chapter to the thermodynamics of computation: we’ve long known that logic operations and memory accesses always consume energy, whether in silicon or in protein-and-salt-water like the human brain. However the human brain has far, far more neurons and synapses than even the largest current AI server farms have GPUs, yet consumes around 20 Watts as opposed to AI’s 50+ Megawatts. Understanding what’s responsible for this immense efficiency gap is crucial for creating a more sustainable next generation of AI, and the answer may lie in new architectures called ‘neuromorphic’ because they mimic biological neurons.

Individual metal-on-silicon-oxide transistors aren’t six orders of magnitude more power-hungry than biological neurons, so other factors must be responsible for the huge difference. One factor is that biological neurons are analog rather than digital, and another is that they act upon data in the same place that they store it. In contrast the CMOS GPUs in AI servers are examples of von Neumann architecture, with processing logic separated from memory, and program code from data. But the MOSFET transistors they’re made from are inherently analog, operated by varying voltages and currents, so the digital data they manipulate gets continuously converted back and forth between the domains, at great energy cost. 

Neuromorphic AI hardware designers try to bring data and processing closer together. Intel introduced its Loihi 2 research chip, with 128 neuromorphic cores and 33MB of on-chip SRAM, which communicates via trains of asynchronous voltage ‘spikes’ like those in biological neurons. Steve Furber (of ARM fame) works at Manchester University on a neuromorphic system called Spinnaker that has tens of thousands of nodes each with 18 ARM cores and memory, also using spike-based communication. These schemes do reduce data access overhead, but they remain digital devices, and to approach biological levels of energy economy will require a still more radical step into purely analog computation that exploits the physics of the chip material itself. 

The US firm Mythic’s AMP (Analog Matrix Processor) chip employs a 2D grid of tunable resistors whose values encode the weights for an AI model, whereupon it relies on Kirchoff’s Laws to in effect multiply-and-add the analog input voltages and perform convolutions. However AMP is still fabricated in CMOS. A more radical next step would be to implement this resistive analog computation using low-power ‘spintronic’ memristors – devices in which the orientation of magnetic spins represent bits as in modern hard disks. One way to implement non-volatile memristors is by FTJs (Ferroelectric Tunneling Junctions) formed by sandwiching nano-thin magnet/insulator/magnet layers which can be fabricated using existing semiconductor processing. These devices can be written to and switched cumulatively like real neurons, and read-out non-destructively using very little power. 

The Dutch physicist Johan Mentink used a recent Royal Institution lecture (https://youtu.be/VTKcsNrqdqA?si=ZRdxeyP4B-hfUw3X) to announce neuromorphic computing experiments in Holland that employ two-dimensional cross-bar grids of memristors, organised into a network of  ‘Stochastic Ising Machines’ that propagates waves of asynchronous random noise whose interference yields the spike trains that transmit information. The Dutch researchers claim such devices can potentially be scaled linearly with the number of synaptic connections, reducing power consumption by factors of 1000s. I love the idea of working with rather than against noise, which certainly feels like what our brains might be doing… 

[Dick Pountain’s neurons are more spiky than most]