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A DIY microscope made out of LEGO bricks and smartphone lenses could be a powerful learning tool, teaching children not only how to use microscopes, but also how they work.

Seeing is learning: Microscopes are an essential scientific tool, right up there with bunsen burners and petri dishes, which means they’re also essential to any child’s science education.

But even when young people have access to microscopes, they’re often only taught how to use the instruments — put a slide here, look through there — and not how they actually work.

We have just checked the Tesla estimated delivery times (for new orders) of all four electric car models available in the U.S.

There are some interesting findings, as the hectic extension of delivery times has slowed down, and in some cases, even stopped or reversed. The prices have also remained unchanged since November 12.

Let’s start with the Model 3. The queue for the entry-level RWD version with an LFP battery appears to decrease as the estimated delivery time is the same as over one and a half months ago (June or October, depending on the wheel option). The Long Range AWD and Performance versions moved up a bit — to March and February. As we can see, the higher price/higher margin versions are prioritized (it will be common for all models).

Indeed, nothing like this has ever been attempted in space before ensuring that we hold our breaths each time the JWTS embarks on the next steps of its six-month journey to fully transform into its final configuration and begin its science mission. Now, NASA is reporting that the telescope just successfully completed another step in its impressive transformation.

“With the successful extension of Webb’s second sunshield mid-boom, the observatory has passed another critical deployment milestone. Webb’s sunshield now resembles its full, kite-shaped form in space,” said NASA in a statement.

Let there be darkness.

That is the potential catchphrase for those that are concerned about nighttime light pollution.

More formerly known as Artificial Light At Night (ALAN), there is an ongoing bruhaha that our modern way of living is generating way too much light during the evening darkness. It is an ongoing issue and the amount of such pollution is likely to keep on increasing due to further industrialization and expansion of societies into additional geographical areas.

In short, you can expect more light to be emitted in existing populated areas, along with nighttime light being unleashed in regions that had so far not been especially well lit due to insufficient means or lack of a light-producing populace. When you start adding more office buildings, more homes, more cars, more lampposts, and the like, this all translates into a tsunami of unbridled light at night.

You might be puzzled as to why the mere shepherding of artificial light is considered a pollution monstrosity.

Tang Jie, the Tsinghua University professor leading the Wu Dao project, said in a recent interview that the group built an even bigger, 100 trillion-parameter model in June, though it has not trained it to “convergence,” the point at which the model stops improving. “We just wanted to prove that we have the ability to do that,” Tang said.


Ironically, China is a competitor that the United States abetted. It’s well known that the U.S. consumer market fed China’s export engine, itself outfitted with U.S. machines, and led to the fastest-growing economy in the world since the 1980s. What’s less well-known is how a handful of technology companies transferred the know-how and trained the experts now giving the United States a run for its money in AI.

Blame Bill Gates, for one. In 1992, Gates led Microsoft into China’s fledgling software market. Six years later, he established Microsoft Research Asia, the company’s largest basic and applied computer-research institute outside the United States. People from that organization have gone on to found or lead many of China’s top technology institutions.

China is a competitor that the United States abetted. A handful of U.S. tech companies transferred their know-how and trained some of China’s top AI experts.