Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI – Page 1,164

The digital dark matter clouding AI in genome analysis

Artificial intelligence has entered our daily lives. First, it was ChatGPT. Now, it’s AI-generated pizza and beer commercials. While we can’t trust AI to be perfect, it turns out that sometimes we can’t trust ourselves with AI either.

Cold Spring Harbor Laboratory (CSHL) Assistant Professor Peter Koo has found that scientists using popular computational tools to interpret AI predictions are picking up too much “noise,” or extra information, when analyzing DNA. And he’s found a way to fix this. Now, with just a couple new lines of code, scientists can get more reliable explanations out of powerful AIs known as . That means they can continue chasing down genuine DNA features. Those features might just signal the next breakthrough in health and medicine. But scientists won’t see the signals if they’re drowned out by too much noise.

So, what causes the meddlesome noise? It’s a mysterious and invisible source like digital “.” Physicists and astronomers believe most of the universe is filled with dark matter, a material that exerts gravitational effects but that no one has yet seen. Similarly, Koo and his team discovered the data that AI is being trained on lacks critical information, leading to significant blind spots. Even worse, those blind spots get factored in when interpreting AI predictions of DNA function. The study is published in the journal Genome Biology.

ChatGPT creates mutating malware that evades detection

A polymorphic defense and a hyperintelligence that could always adapt to rapid malware changes would be need much like sending The Vision from Ironman seemed to counter the ultron threat. Another scenario is that we could have chat gpt defensive anti-virus that could be local like we have today. The dark side to this AI still is a chaos chat gpt where it always changing not just polymorphic but changing in all ways but still an AI cyberdefense would make this threat lower.

Mutating, or polymorphic, malware can be built using the ChatGPT API at runtime to effect advanced attacks that can evade endpoint detections and response (EDR) applications.

Meet Chaos-GPT: An AI Tool That Seeks to Destroy Humanity

Basically I have talked about how chaos gpt poses a great threat to current cyberdefenses and it still does but there is great promise of a god like AI that can a powerful force of good. This could also become a greater AI arms race that would need even more security measures like an AI god that can counter state level or country level threats. I do think this threat would come regardless when we try to reach agi but chat gpt also shows much more promising results as it could be used a god like AI with coders using it aswell as AI coders.

Chaos-GPT, an autonomous implementation of ChatGPT, has been unveiled, and its objectives are as terrifying as they are well-structured.

A Generative AI Upped Worker Productivity and Satisfaction—and the Lowest-Skilled Benefited Most

Perhaps not surprisingly, the AI was the most helpful for the least-skilled workers and those who had been with the company for the shortest time. Meanwhile, the highest-skilled and most experienced agents didn’t benefit much from using the AI. This makes sense, since the tool was trained on conversations from these workers; they already know what they’re doing.

“High-skilled workers may have less to gain from AI assistance precisely because AI recommendations capture the knowledge embodied in their own behaviors,” said study author Erik Brynjolfsson, director of the Stanford Digital Economy Lab.

The AI enabled employees with only two months of experience to perform as well as those who’d been in their roles for six months. That’s some serious skill acceleration. But is it “cheating”? Are the employees using the AI skipping over valuable first-hand training, missing out on learning by doing? Would their skills grind to a halt if the AI were taken away, since they’ve been repeating its suggestions rather than thinking through responses on their own?

AI and humans collaborate on first ChatGPT-designed robot

Is there anything ChatGPT can’t do? Yes, of course, but the list appears to be getting smaller and smaller. Now, researchers have used the large language model to help them design and construct a tomato-picking robot.

Large language models (LLMs) can process and internalize huge amounts of text data, using this information to answer questions. OpenAI’s ChatGPT is one such LLM.

In a new case study, researchers from the Delft University of Technology in the Netherlands and the Swiss Federal Institute of Technology (EPFL) enlisted the help of ChatGPT-3 to design and construct a robot, which might seem strange considering that ChatGPT is a language model.

THE BIG RESET: Use AI To Build Wealth & GET AHEAD Of 99% Of People with Peter Diamandis & Salim Ismail

Imagine building a billion-dollar company that competes with the biggest companies in the industry, and doing it with a modest 3 person team powered by AI.

We’re living through a time of rapid change and endless possibilities and opportunities, what are you going to do about it?

While the fear of AI has a lot of people scrambling, anxious, or in denial about the implications of AI in their life and ability to earn a living and provide for their families, there are people like Peter Diamandis, Salim Ismail, and Tom Bilyeu that are going to leverage AI to the max to create a massive impact. Peter Diamondis and Salim Ismail have co-authored the book Exponential Organizations 2.0 where they break down the framework and key differences to exponential growth and success between Fortune 500 companies and some of the most successful unicorn companies of our time.

Honda’s Riding Assist-e Self Balancing Electric Motorcycle Concept

The Honda Riding Assist is an electric vehicle that has a low center-of-gravity and a very low seat height. In a global debut at CES, Honda unveiled the Honda Riding Assist motorcycle, which leverages our robotics technology to create a self-balancing motorcycle that greatly reduces the possibility of failing over while the motorcycle is at rest.

source/image: Alpha SQUAD official.

Why We Need More Collaboration Between EdTech And AI Developers

The current education landscape requires close collaboration between edtech and AI developers to leverage their expertise and maximize the impact of AI technology in the sector. It also aims to avoid the negative consequences of redundant efforts, wasted resources and less effective solutions. By effectively applying best practices such as clear communication, alignment of goals, and interdisciplinary collaboration, edtech and AI developers can develop innovative, scalable and effective solutions. The “AI and the Future of Learning: Expert Panel Report” underscores key strategies for successful collaboration between edtech and AI developers. The report highlights key strengths and weaknesses of AI as well as the respective opportunities and barriers to employing AI technologies in the education sector.

Education plays a critical role in promoting social and economic development in a region, and when communities recognize its potential, they are more likely to support educational reforms. These reforms can address any challenges in the sector, such as funding constraints, lack of access to quality education and cultural attitudes that may deny education to particular groups. With the increased adoption of AI in the education sector, potential future developments—including ITS, adaptive assessment, gamification and the use of machine learning—can promote the efficiency of personalized learning.

In the long run, the collaboration between edtech and AI developers holds great potential for transforming education and improving learning outcomes. For this to happen, it is necessary to establish industry standards for AI in education, foster interdisciplinary collaboration between educators and AI experts, and invest in research on AI’s impact on learning outcomes. In this way, we can ensure that AI-powered tools are used effectively and ethically to improve student learning in the 21st century.

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