A retro video gaming devotee has showcased Lara Croft adventuring in and among ancient tombs on a humble ESP32-P4 microcontroller. This highly affordable device (available as a sub-$25 dev board) packs a pair of 32-bit 400 MHz RISC cores and delivers a slick, playable 1,024 x 600 pixel experience for TheAlexKid777, yet consumes roughly 1 watt at peak. It is good to see someone having video-gaming fun with cheap, power-sipping new tech in 2026.

When it launched in the mid-90s, Tomb Raider quickly became a classic by successfully capturing the add-a-third-dimension-to-all-games-and-IPs trend while delivering an eminently enjoyable adventure game. Not all games were better because they were in 3D rather than 2D. Far from it. Now the compute power required to run a title like OpenLara doesn’t require an expensive and power-hungry game console - a cheap dev board that typically consumes milliwatts is capable enough today.

But the high-efficiency low-wattage gaming feat described above is just half the story. The other phenomenon demonstrated here is the beefing up of commonly available microcontrollers. Developers no longer need to be extremely resource thrifty when coding for these humble devices. They now pack plenty of horsepower to spare.

In the case of Espressif’s ESP32-P4, there is “a dual-core RISC-V CPU featuring AI instruction extensions, an advanced memory subsystem, and integrated high-speed peripherals,” the maker highlights. There’s also up to 64MB PSRAM, 768KB SRAM, an FPU, DSP, ISP, 55 programmable GPIOs, and more. It sounds almost like an original Tomb Raider era dream.

In TheAlexKid777’s demo, this hardware is attached to the back of what looks like a 7- or 8-inch LCD. It runs OpenLara at 320 x 240 pixels, which is PPA hardware scaled to 1,024 x 600 pixels. The game also features stereo audio pumped through the dev board’s ES8311 codec, and it's controlled via a connected USB keyboard.

We’ve previously reported on various ESP32 family microcontrollers being used to: power a retro Mac emulator, host a tiny ad-blocking dongle, and even run a 28.9 million parameter LLM. Some of these projects use far cheaper ESP32 microcontrollers, too, starting at $5.

Late last week, Google announced that scientists had, for the first time, “mapped the complete brain and central nervous system of an adult male fruit fly.” On Monday, software engineers were already demonstrating the full MaleCNS v1.0 fruit fly connectome being trained to play Doom, as well as Super Mario 64. In light of these developments, perhaps it is time to amend Arthur C. Clarke’s Third Law. We suggest something similar to ‘Any sufficiently advanced new technology will immediately be forced to play Doom.’

Let’s look at this story in its natural chronological order. Scientists have been using fruit flies for research for over a century. The winged insects have a strong history in the avenues of genetic research. The humble fruit fly is still relevant in the 2020s in genetics, neuroscience, and more.

Now, for the first time, the complete brain and central nervous system of an adult male fruit fly have been fully mapped. Google Research scientists worked alongside HHMI Janelia Research Campus and the scientific community to achieve this milestone. In the social media post outlining the achievement, Google claimed that AI was used “to combine millions of 2D images into 3D neural shapes, reconstructing a record-breaking 166,000+ neurons.” That’s somewhat below the estimated 86 billion neurons in the human brain. AI data centers are going to need more RAM, folks.

This scientific breakthrough is going to “accelerate our understanding of the brain, and is a major milestone in neuroscience,” noted Google last Thursday. By Tuesday, it was already being trained to play classic video games.

We’ve seen software engineer Alex Wormuth and ‘C++ ragebaiteur’ Jessica Paquette already demonstrate fly-brain video game training. Their fly-brain tinkering focuses on Doom and Mario 64, respectively.

Of their Doom training efforts, Wormuth says that “Each Doom frame stimulates sensory neurons. Neural activity is mapped to game controls. Damage triggers a stimulus to two PPL101 dopamine cells as reinforcement.” The dev closes their tweet with the question “Will the fly learn to survive?” The code is fully open source, and you can also watch the training progress of the 166,700 neurons live.

Paquette’s short video clip shows Mario repeatedly taking off and bumping into a wall. If it were bumping into a window, it would be exhibiting the pinnacle of fly-brain intelligence. We also have the code to this fly-brain video gaming project, which was “literally 100% vibe coded with GPT Astra… just for fun.” Hopefully non-coders/tinkerers will get updates on the success of this training via Paquette’s socials.