Measuring Trees Via Satellite Actually Takes A Great Deal Of Field Work

Figuring out what the Earth’s climate is going to do at any given point is a difficult task. To know how it will react to given events, you need to know what you’re working with. This requires an accurate model of everything from ocean currents to atmospheric heat absorption and the chemical and literal behavior of everything from cattle to humans to trees.

In the latter regard, scientists need to know how many trees we have to properly model the climate. This is key, as trees play a major role in the carbon cycle by turning carbon dioxide into oxygen plus wood. But how do you count trees at a continental scale? You’ll probably want to get yourself a nice satellite to do the job.

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A Straightforward AI Voice Assistant, On A Pi

With AI being all the rage at the moment it’s been somewhat annoying that using a large language model (LLM) without significant amounts of computing power meant surrendering to an online service run by a large company. But as happens with every technological innovation the state of the art has moved on, now to such an extent that a computer as small as a Raspberry Pi can join the fun. [Nick Bild] has one running on a Pi 4, and he’s gone further than just a chatbot by making into a voice assistant.

The brains of the operation is a Tinyllama LLM, packaged as a llamafile, which is to say an executable that provides about as easy a one-step access to a local LLM as it’s currently possible to get. The whisper voice recognition sytem provides a text transcript of the input prompt, while the eSpeak speech synthesizer creates a voice output for the result. There’s a brief demo video we’ve placed below the break, which shows it working, albeit slowly.

Perhaps the most important part of this project is that it’s easy to install and he’s provided full instructions in a GitHub repository. We know that the quality and speed of these models on commodity single board computers will only increase with time, so we’d rate this as an important step towards really good and cheap local LLMs. It may however be a while before it can help you make breakfast.

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Gold Recovery From E-Waste With Food-Waste Amyloid Aerogels

A big part of the recycling of electronic equipment is the recovery of metals such as gold. Usually the printed circuit boards and other components are shredded, sorted, and then separated. But efficiently filtering out specific metals remains tricky and adds to the cost of recycling. A possible way to optimize the recovery of precious metals like gold could be through the use of aerogels composed out of protein amyloids to which one type of metal would preferentially adsorb. According to a recent research article in Advanced Materials by [Mohammad Peydayesh] and colleagues, such aerogels could be created from protein waste from the food industry.

The adsorption mechanism of the protein amyloids is a feature of these proteins which form chelants, which are structures that can effectively bond to metal ions. These are usually organic compounds, and are used in certain medical treatments where heavy metal poisoning is involved (chelation therapy). By having these protein amyloids in an aerogel structure, the surface area for adsorption is maximized, which in the research article is said to have an efficiency of 93.3% for gold recovery, while leaving the other metals in the aqua regia solution (nitric and hydrochloric acid) mostly untouched.

Of note here is that although the food waste protein angle is taken, the experiment used whey protein. This is also one of the most popular food supplements in the world, to the point that microbial production of whey is a thing now. Although this doesn’t invalidate the aerogel chelation approach to e-waste recycling, it’s a curious omission in the article that does not appear to be addressed.