The **ESP32** is a low-cost, low-power microcontroller with integrated Wi-Fi and Bluetooth, ideal for DIY electronics projects involving LED control due to its ability to drive addressable LEDs like WS2812 efficiently.[4][5]

Multiple **ESP32** boards can synchronize LED effects using methods like ESP-NOW, UDP packets over Wi-Fi, or RTC with NTP time sync to ensure parallel operation without delays, allowing dynamic matrix displays.[1][3]

Direct comparisons of gas prices per gallon to electricity prices per kWh are misleading because EVs and gas vehicles have different energy efficiencies and consumption rates; a better approach is comparing **cost per mile**, which accounts for real-world usage and reveals EVs' lower costs, often half or less than gas.[1][2][3]

Home charging costs about $0.16-$0.18 per kWh, making a full charge for a 72 kWh battery around $12-$13 or 5-6 cents per mile, versus $0.25-$0.47 per kWh at public stations ($18-$34 per charge) and 11 cents per mile for gas at $3-$4 per gallon; annual savings can exceed $1,000 for typical drivers.[1][2][7]

South Korean exchanges Upbit, Bithumb, and Coinone are delisting FLOW due to unresolved security concerns and potential risks to users. The delisting stems from South Korea's Virtual Asset User Protection Act, which fully came into effect in July 2024 and mandates exchanges to implement rigorous listing and ongoing monitoring standards. Specifically, exchanges cited historical security incidents and vulnerabilities in the Flow ecosystem as reasons for the caution designation, which ultimately led to the delisting decision. Under this strict regulatory framework enforced by the Financial Services Commission (FSC) and Financial Intelligence Unit (FIU), exchanges bear greater liability for user losses and therefore err on the side of caution regarding projects with publicly questioned security histories.

The delisting by major South Korean exchanges significantly reduces liquidity and accessibility for FLOW within a key market. Upbit and Bithumb represent major gateways for South Korean investors, and their removal effectively cuts off a significant fiat on-ramp and trading venue. The delisting typically triggers short-term price volatility as holders on these exchanges seek to exit positions before trading halts. Long-term implications include potential reputational damage to the FLOW project, which may affect its credibility with other global exchanges and institutional partners. Additionally, projects and decentralized applications built on the Flow blockchain may face reduced visibility for Korean users, a key demographic in the NFT and gaming sectors, and other exchanges globally may initiate their own compliance reviews, creating a domino effect.

Vibe coding is an AI-assisted approach to app creation that enables users to build custom applications without requiring traditional programming knowledge or syntax. Instead of writing code manually, users describe their app ideas in natural language, and AI interprets these descriptions to generate functional applications. This democratizes app development by removing technical barriers that typically require years of coding education.

Vibe coding would complement Samsung's Galaxy AI ecosystem, which already includes agentic AI capabilities that automate multi-step tasks across apps. The Galaxy S26's Gemini integration and upgraded Bixby conversational agent demonstrate Samsung's commitment to natural language interaction. Vibe coding would extend this principle to app creation itself, allowing users to leverage the same conversational AI interface to design custom applications tailored to their specific needs, building on the foundation of Galaxy AI's task automation and cross-app coordination.

Concept bottleneck modeling (CBM) is a method that forces AI systems to explain their decisions using human-understandable concepts rather than operating as a 'black box.' Instead of showing only inputs and outputs, CBM requires the model to identify and use specific concepts—such as 'clustered brown dots' or 'variegated pigmentation' in medical imaging—to justify its predictions. This approach makes AI reasoning transparent and trustworthy, which is especially important in high-stakes fields like medical diagnostics where users need to verify whether an AI recommendation is reliable before acting on it.

The new MIT technique automatically extracts concepts that a model has already learned during training on a specific task, rather than relying on pre-defined concepts chosen by human experts. This is significant because pre-defined concepts may be irrelevant or lack sufficient detail for the task at hand, reducing accuracy. By extracting task-specific concepts and limiting the model to use only the five most relevant ones per prediction, the new method achieves higher accuracy while providing clearer, more concise explanations. Testing on tasks like bird species prediction and skin lesion identification showed this approach outperformed existing concept bottleneck models while generating more applicable explanations.

The IBF ruled that Opetaia would be stripped of his title if he proceeded with the fight in Las Vegas, making only the Zuffa cruiserweight belt available unless the IBF reversed its decision.

Zuffa Boxing is a promotional entity presenting its fourth event (Zuffa Boxing 4) at the Meta Apex in Las Vegas; the main event featured Jai Opetaia against Brandon Glanton for the inaugural Zuffa cruiserweight title.

A metasurface is an ultra-thin chip patterned with tiny structures smaller than the wavelength of light, enabling precise control over light's properties such as phase, polarization, and direction without bulky components.

The chip uses nonlinear light generation via third-harmonic generation, converting 1530 nm infrared light to 510 nm green light through a quasi-bound state in the continuum resonance that amplifies the input; steering is achieved by rotating nanostructures to impart a position-dependent phase, controlled by changing the input light's polarization.