Poki vs Raspberry Pi

Green Game Jam 2026: Meet Poki’s Winners

Poki announces the winners of the Green Game Jam 2026, a sustainability-focused game jam, with a new blog post dated 22 SEP 2026.

3AM Experiences' Roblox Games Surpass 1 Billion Plays

3AM Experiences, a game studio founded in 2015, announced that its games on Roblox have surpassed 1 billion total plays. The milestone was shared on May 1st, 2026, and credited to years of development and community support. The company, co-founded by Mistik and Nation, focuses on instant-play multiplayer and UGC experiences across web, mobile, and Roblox. Its portfolio includes titles like Diep.io and Mope.io, which were acquired from Addicting Games in 2024. The studio has also collaborated with partners such as CrazyGames, Poki, and Xsolla. 3AM Experiences plans to continue expanding its Roblox content and exploring new ideas.

• 3AM Experiences' Roblox games surpassed 1 billion plays, announced on May 1st, 2026.
• The studio was founded in 2015 by co-founders including Mistik and Nation.
• The company acquired Mope.io and Diep.io in 2024 from Addicting Games.

Make it Meme launches mobile app after web success

Make it Meme, a multiplayer browser party game by prealpha, is expanding to mobile after amassing over 600 million games played since its March 14, 2021 web launch. The dedicated app entered public beta on Android in mid-August 2026 and the iOS version launched fully; a full Android release is targeted for September 2026. The studio (prealpha) monetises primarily via web advertising, tiered subscriptions (including an Elite plan) and an in-game currency (MiM Coins). The team emphasises keeping web and mobile experiences closely aligned, cross-play support, minimal personal data collection (age gate for under-13s), and continued investment in moderation and ad partner testing.

• Make it Meme has recorded more than 600 million games played since its web release on March 14, 2021.
• The dedicated Make it Meme mobile app entered Android public beta in mid-August 2026; the iOS app has launched in full and a wider Android release is aimed for September 2026.
• Around 60% of Make it Meme's web traffic comes from mobile devices and 37% comes from iPhones.

Open-Source Kit Revives iPods with Modern Features

The article introduces Sprout Pi and Sprout Pico, open-source mainboard replacement kits for iPods and iPod Mini, created by Certain Things. These kits replace the original motherboard to add Bluetooth, Wi-Fi, USB-C, a Micro-SD slot supporting up to 2TB, and a new battery lasting up to 40 hours. The third and fourth generation iPods are targeted by Sprout Pi, while Sprout Pico is designed for the iPod Mini. The project preserves the iconic clickwheel and display for a vintage feel. Hardware is based on a Raspberry Pi, and the software will be fully open-sourced on GitHub upon release. The kits were presented on Certain Things' website and Crowd Supply, with the launch date yet to be announced. This appeal to tech enthusiasts and modders revives classic devices for modern daily use.

• Certain Things introduced Sprout Pi and Sprout Pico, open-source mainboard replacement kits for iPods.
• Sprout Pi targets 3rd and 4th generation iPods, Sprout Pico for iPod Mini.
• The kits add Bluetooth, Wi-Fi, USB-C, Micro-SD slot up to 2TB, and a 40-hour battery.

Smart Pill Reminder with YOLOv8 on Raspberry Pi

This technical tutorial demonstrates how to build a real-time pill identification and reminder system using YOLOv8 for multi-pill detection and semantic segmentation, running on a Raspberry Pi. The guide covers system architecture (edge inference with OpenCV), training a YOLOv8 segmentation model, exporting optimized model formats (OpenVINO/NCNN) for Raspberry Pi deployment, and using MQTT (Paho-MQTT) to trigger physical alarms or send status updates to apps or dashboards. The article also outlines production considerations such as model quantization, secure streaming, and OTA updates.

• The tutorial builds a real-time pill identification and reminder system using YOLOv8 for detection and semantic segmentation on a Raspberry Pi.
• Training example uses Ultralytics' YOLOv8 segmentation model (example: model.train(data='pills.yaml', epochs=50, imgsz=640, device='cpu')).
• For Raspberry Pi deployment, the article recommends exporting models to OpenVINO or NCNN to improve inference FPS.