Pema Tseden was the founder and builder of Tibetan cinema [The Economist]
“It’s a sad lesson. No matter how blood-soaked you are, you can find a road to diplomatic redemption”—Assad’s comeback [The Economist Podcasts]
Zelensky joins Ukraine talks on final day at G7 [BBC News]
California’s Newsom Says State Needs Infrastructure Boom Bigger Than Any in Decades [Bloomberg]
Hiroshima G7 marks costs of war and welcomes Ukraine's Zelenskiy [Reuters]
Khartoum’s outskirts attacked as Sudan war enters sixth week [AL-Jazeera News]
Working for the Weekend Plans [New Yorker]
I took my own advice and bought a last-gen iPhone — I regret nothing / Sometimes the best new phone for you is the one that launched a year and a half ago. [The Verge]
Everything old is new again [Vox]
This episode is just an excuse to talk about Zelda and other TC news [TechCrunch]
This startup says its first fusion plant is five years away. Experts doubt it. [MIT Technology Review]
Adidas will finally start to move its $1.3 billion mountain of unsold Yeezy sneakers within days [Insider]
As machine learning evolves, new applications are being discovered to push the boundaries of what can be accomplished with AI. Specifically, how machine learning technology can be integrated into our daily lives.
From @Kurtis Pykes, Data Science and AI Blogger, uncover one of those developments—TinyML—which involves deploying machine-learning models on small devices with low power consumption.
Despite the many instances of machine learning in daily life (virtual assistants, Netflix recommendations, etc.) there are still several areas the technology has failed to reach, caused largely by the demand for high-performance computing power. If ML is to expand and democratize, a solution to run inference on smaller, more resource-constrained devices is required. The pursuit of this solution has led to the subfield—Tiny Machine Learning (TinyML).
In this article, we will:
👉 Define TinyML and its benefits
👉 Cover some applications of TinyML
👉 Discuss the workflow requirements involved for TinyML applications
👉 What you need to get started with this emerging field of machine learning
Discover more ➡️ https://bit.ly/3mRdpiv [LinkedIn] #DataCamp
Sound vibrations can encode and process data like quantum computers do [New Scientist]
Fast X review – more overcranked nonsense with Vin Diesel and co [The Guardian]
The E-Sports World Is Starting to Teeter [The New York Times]
Dominion Dominos Fall: More Fox News Layoffs [Huffington Post]
How to Be More Creative [The Atlantic]
Can You Save The World? [FiveThirtyEight]
Opinion: Here is how to think about Biden’s age [The Washington Post]
Le G7 affirme que toute coercition économique « aura des conséquences », visant la Chine sans la nommer [Le Monde]
NASA rover video shows astonishing view into Mars crater [Mashable]
How Space Companies Plan to Build Roads and Bases on the Moon [VICE News]
Inside the Pentagon’s New “Perception Management” Office to Counter Disinformation [The Intercept_]
Swastika Mountain needed a new name. Here’s how it got one. [National Geographic]
'Love to Love You, Donna Summer' documents the disco queen — but at a distance [NPR]
Gavin Newsom wants to make it easier to build roads, dams and more. What’s in his plan? [CapRadioNews] #Infrastructure
En Amérique latine, le non-alignement au service de la paix [Le Monde diplomatique]
Russia’s War in Ukraine: Updates and analysis on battlefield strategy and diplomacy [Foreign Policy]
Can China Thread the Needle on Ukraine? — Beijing Struggles to Balance Its Ties to Russia and Europe [Foreign Affairs]
How Japanese Civilians Are Supporting Ukraine [The Diplomat]
Memories Help Brains Recognize New Events Worth Remembering [Quanta Magazine]

BLOGPOST UPDATE IN PROGRESS

What’s up, everybody! Here are JETLAG RADIO 852 & BENKYO RADIO 852.

Here is a new MIDI keyboard called Nopia, looks interesting.

Until Next Time!