Educators just started recovering from the profound impact of the COVID-19 pandemic. Some studies assess that the learning loss may never be recovered. However, a new challenge has crashed on the shores of education — AI — which could be even more impactful. In this post, we look at the challenges that AI brings to education, some ideas, and steps being taken.
A look at the newly announced Generative AI guidance from UNESCO, and others. An explanation of what they mean for application.
The explosive recent growth of AI tools to generate text, images, or audio relies on gargantuan amounts of information.
That information doesn’t come for free. It can exact high – and unequal – costs in terms of energy, water, and labor, though these costs are largely invisible to users.
In terms of energy, generative AI models typically depend on extremely large-scale cloud providers, which use chips with more transistors that require at least 10 times as much energy as traditional versions. Unsurprisingly, models that use more training data and contain more parameters tend to guzzle more energy.
The 2 SOPS or 2nd Space Operations Squadron commander, Lt Col Robert Wray… More.
Of all the missions the Space Force performs daily for a grateful nation, there is none more ubiquitous and essential than GPS. Today’s soldiers and sailors depend on reliable, accurate, and secure GPS as much as they do any weapon they employ. Meanwhile, the rest of the world is just as dependent on GPS to enable basic mobility and underpins every other sector of the modern global economy. The criticality of secure global navigation and timing to both warfighting and the national economy makes it unique – we simply could not go a day without space. In so few words, GPS’ future is ground zero for the new space race.
The 2 SOPS or 2nd Space Operations Squadron commander, Lt Col Robert Wray reminds me that “14 of the 16 critical infrastructures designated by the Department of Homeland Security rely on 24/7 GPS to operate for the country.” But the newest GPS satellites in use today are the same school bus sized ones Gen. Hyten has lamented are, “juicy targets” for our adversaries – marvels of modern engineering, yes, but no longer sufficient to meet modern needs.
Alternatives to GPS, categorically called Global Navigation Satellite Systems (GNSS), are growing rapidly because the old GPS system we rely on offers neither the precision nor security needed in an increasingly autonomous, rule based, and precisely timed world. What exactly needs to change then, aside from smaller, faster satellites as technology becomes more efficient and readily available? There are major challenges with the current system that today’s Guardians are already working on. But to usher in a new and improved GPS capability, the government needs to adopt artificial intelligence and machine learning to enhance squadron operations, work to better integrate commercial software into current GPS constellation to get the most out of current capabilities, and continue to invest in the next generation of leaders. Private capital has begun aligning with companies aiming to solve these future deficiencies, in a race against pacing threats like China and Russia.
Llama 2 Long is an extension of Llama 2, an open-source AI model that Meta released in the summer.
While Meta Platforms unveiled several new AI-powered features for its popular apps like Facebook, Instagram, and WhatsApp at its annual Meta Connect event in California this week, the most impressive innovation from the social media giant may have gone unnoticed by many.
A team of Meta researchers quietly published a paper introducing Llama 2 Long, a new AI model that can generate coherent and relevant responses to long user queries, surpassing some of the best competitors in the field.
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AI can also help develop objective risk stratification scores, predict the course of disease or treatment outcomes in CLD or liver cancer, facilitate easier and more successful liver transplantation, and develop quality metrics for hepatology.
Artificial Intelligence (AI) is an umbrella term that covers all computational processes aimed at mimicking and extending human intelligence for problem-solving and decision-making. It is based on algorithms or arrays of mathematical formulae that make up specific computational learning methods. Machine learning (ML) and deep learning (DL) use algorithms in more complex ways to predict learned and new outcomes.
AI-powered liver disease diagnosis Machine learning for treatment planning Predicting disease progression The future of hepatology References Further reading
Hepatology largely depends on imaging, a field that AI can fully exploit. Machine learning is being pressed into play to extract rich information from imaging and clinical data to aid the non-invasive and accurate diagnosis of multiple liver conditions.
While ChatGPT and its associated AI models are clearly not human (despite the hype associated with its marketing), if the updates perform as shown, they potentially represent a significant expansion in capabilities for OpenAI’s computer assistant:
[📸: Getty Images]
On Monday, OpenAI announced a significant update to ChatGPT that enables its GPT-3.5 and GPT-4 AI models to analyze images and react to them as part of a text conversation. Also, the ChatGPT mobile app will add speech synthesis options that, when paired with its existing speech recognition features, will enable fully verbal conversations with the AI assistant, OpenAI says.
OpenAI says the new image recognition feature in ChatGPT lets users upload one or more images for conversation, using either the GPT-3.5 or GPT-4 models. In its promotional blog post, the company claims the feature can be used for a variety of everyday applications: from figuring out what’s for dinner by taking pictures of the fridge and pantry, to troubleshooting why your grill won’t start.
Insilico Medicine, a clinical-stage generative AI-driven drug discovery company has announced that the company has used Microsoft BioGPT to identify targets against both the aging process and major age-related diseases.
Longevity. Technology: ChatGPT – the AI chatbot – can craft poems, write webcode and plan holidays. Large language models (LLMs) are the cornerstone of chatbots like GPT-4; trained on vast amounts of text data, they have been contributing to advances in diverse fields including literature, art and science – but their potential in the complex realms of biology and genomics has yet to be fully unlocked.
Forward-looking: While AI has been at the forefront of most tech industry conversations this year, the new wave of generative AI is still far off the concept of an artificial general intelligence (AGI). However, legendary developer John Carmack believes such a technology will be shown off sometime around 2030.
Carmack, of course, is best known as the co-founder of id Software and lead programmer of Wolfenstein 3D, Doom, and Quake. He left Oculus in December last year to focus on Keen Technologies, his new AGI startup.
In an announcement video (via The Reg) revealing that Keen has hired Richard Sutton, chief scientific advisor at the Alberta Machine Intelligence Institute, Carmack said the new hire was ideally positioned to work on AGI.
Scientists at the University of Washington have developed flying robots that change shape in mid-air, all without batteries, as originally published in the research journal Science Robotics. These miniature Transformers snap into a folded position during flight to stabilize descent. They weigh just 400 milligrams and feature an on-board battery-free actuator complete with a solar power-harvesting circuit.
Here’s how they work. These robots actually mimic the flight of different leaf types in mid-air once they’re dropped from a drone at an approximate height of 130 feet. The origami-inspired design allows them to transform quickly from an unfolded to a folded state, a process that takes just 25 milliseconds. This transformation allows for different descent trajectories, with the unfolded position floating around on the breeze and the folded one falling more directly. Small robots are nothing new, but this is the first solar-powered microflier that allows for control over the descent, thanks to an onboard pressure sensor to estimate altitude, an onboard timer and a simple Bluetooth receiver.