Trending Now Look Up Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Say More Mashable Selects Mashable Voices Safety Net Creator Hub Versus Gift Ideas For Everyone On Your List Switch Off In My Bag All Series This innovation could help address both pollution and hunger. But would you eat one? Amanda Yeo is an Assistant Editor at Mashable, covering entertainment, culture, tech, science, and social good. Based in Australia, she writes about everything from video games and K-pop to movies and gadgets. Scientists have transformed PET plastic into nutritious edible cookies, an innovation that could help address both pollution and hunger in one fell swoop.

Plus: how wastewater tracking could help curb measles' rise in the US. Can ChatGPT Health do better? For the past two decades, there's been a clear first step for anyone who starts experiencing new medical symptoms: Look them up online. The practice was so common that it gained the pejorative moniker "Dr. But times are changing, and many medical-information seekers are now using LLMs. According to OpenAI, 230 million people ask ChatGPT health-related queries each week.

It's well documented that AI is a power-hungry technology. But there has been far less reporting on the extent of that hunger, how much its appetite is set to grow in the coming years, where that power will come from, and who will pay for it. For the past six months, MIT Technology Review's team of reporters and editors have worked to answer those questions. The result is an unprecedented look at the state of AI's energy and resource usage, where it is now, where it is headed in the years to come, and why we have to get it right. At the centerpiece of this package is an entirely novel line of reporting into the demands of inference--the way human beings interact with AI when we make text queries or ask AI to come up with new images or create videos.

The cost of making further progress in artificial intelligence is becoming as startling as a hallucination by ChatGPT. Demand for the graphics chips known as GPUs needed for large-scale AI training has driven prices of the crucial components through the roof. OpenAI has said that training the algorithm that now powers ChatGPT cost the firm over 100 million. The race to compete in AI also means that data centers are now consuming worrying amounts of energy. The AI gold rush has a few startups hatching bold plans to create new computational shovels to sell.

In AI development, the dominant paradigm is that the more training data, the better. OpenAI's GPT-2 model had a data set consisting of 40 gigabytes of text. GPT-3, which ChatGPT is based on, was trained on 570 GB of data. OpenAI has not shared how big the data set for its latest model, GPT-4, is. But that hunger for larger models is now coming back to bite the company. In the past few weeks, several Western data protection authorities have started investigations into how OpenAI collects and processes the data powering ChatGPT.

Today's date is April 13th, 2023. Since the public unveiling of ChatGPT couple of months ago, a large language model developed by OpenAI, we have been experiencing a continuous, probably exponential, advancement in AI which could cause the world, as we know it today, to be completely different in just a couple of years. One of the latest ground breaking experiments involved enabling GPT Agents to speak with each other, with a human merely specifying the context of the conversation before hand, e.g. "find a potential cure for cancer" and the two agents would start researching and dig deeper and browse the internet, perform researches, run simulations and do calculations that would be unfeasible for most researchers to do. If we'd compare AI to a human, then it would be only a couple of weeks old.

Ending global hunger has long been a critical goal for the global community. When the United Nations' Sustainable Development Goals were released in 2014, ending hunger, food insecurity and all forms of malnutrition formed SDG2. Though there has been some progress in the fight against hunger – ongoing conflicts, climate change, economic downturns and the COVID-19 pandemic have been major barriers to achieving SDG2. As of 2020, according to the UN, 720 and 811 million people globally faced hunger, and current estimates suggest that 660 million people may still face hunger in 2030. Professor Salah Sukkarieh, a robotics engineer at the University of Sydney's Australian Centre for Field Robotics, will this week speak at the United Nations Food and Agriculture Organization's (FAO) Global Conference on Sustainable Plant Production in Rome (2-4 November).

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Are giant AI language models like GPT-3 or PaLM under-trained? A Deepmind study shows that we can expect further leaps in performance. Big language models like OpenAI's GPT-3, Deepmind's Gopher, or most recently Google's powerful PaLM rely on lots of data and gigantic neural networks with hundreds of billions of parameters. PaLM, with 540 billion parameters, is the largest language model to date. The trend toward more and more parameters stems from the previous finding that the capabilities of large AI models scale with their size.

It's hard to believe it now, but just four short years ago articles on quantum computing were a bit of a dud when it came to catching the attention of mainstream news consumers. Oh what a difference a few years can make. You can't open the science section on Google or Apple News nowadays without seeing a near-equal split between space and quantum physics stories. The world's fallen in love with speculative science again thanks to quantum computing and artificial intelligence, and I couldn't be happier. Attend the tech festival of the year and get your super early bird ticket now! I believe quantum computing has the ability to impact our species in a way that nothing short of the emergence of a physical God or the arrival of an advanced alien benefactor can.