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Artificial Intelligence

Using AI to develop arithmetic algorithms that are more effective

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Using AI, researchers at Google’s DeepMind in London have discovered that matrix multiplication issues can be solved more quickly. The team outlines enhancing math-based algorithms through reinforcement learning in their research that was published in the journal Nature. In the same journal issue, a Research Briefing detailing the work done by the London team was also released.

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In computer programming, math is frequently used to describe and then manipulate representations of real-world phenomena. It can be used to represent nodes in a synthetic network, meteorological conditions, or pixels on a computer screen. Calculations on matrices are one of the main ways that math is used in these situations. Matrixes can be used, for instance, to describe potential movement options in game programming. Matrices are frequently multiplied or added to in order to effectuate such movements; occasionally, both operations are required. This is labor-intensive, especially as the matrices get bigger, therefore computer scientists have devoted a lot of time and effort to creating ever-more-effective algorithms to do the task.

In this new endeavor, the DeepMind researchers questioned whether it may be feasible to deploy an AI system based on reinforcement learning to develop new algorithms with fewer steps than those already in use. They sought inspiration from gaming systems to learn the answer, observing that the majority of them are based on reinforcement learning. The team focused on tree searching after developing a few prototype systems, which is also used in game programming. It gives a system a way to consider multiple options in light of a specific condition. The researchers discovered that turning an AI system into a game allowed for searching for the most effective technique to arrive at a desired outcome—a mathematical result—when used to multiplying matrices.

The system was put to the test by the researchers by having it look for, evaluate, and employ pre-existing algorithms while utilizing incentives to select the most effective one. The system gained knowledge of the elements that affect the effectiveness of matrix multiplication. The researchers then gave the system the freedom to develop its own algorithm in an effort to increase efficiency. The researchers discovered that the algorithms selected by the system were frequently superior than those developed by their human forebears.

Who doesn’t enjoy listening to a good story. Personally I love reading about the people who inspire me and what it took for them to achieve their success. As I am a bit of a self confessed tech geek I think there is no better way to discover these stories than by reading every day some articles or the newspaper . My bookcases are filled with good tech biographies, they remind me that anyone can be a success. So even if you come from an underprivileged part of society or you aren’t the smartest person in the room we all have a chance to reach the top. The same message shines in my beliefs. All it takes to succeed is a good idea, a little risk and a lot of hard work and any geek can become a success. VENI VIDI VICI .

Artificial Intelligence

ChatGPT Will Soon “See, Hear, And Speak” With Its Latest AI Update

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A major update to ChatGPT lets the chatbot respond to images and voice conversations. The AI will hear your questions, see the world, and respond.

OpenAI, the non-profit group behind ChatGPT and DALL-E, announced the “multimodal” update in a blog post on Monday, saying it will add voice and image features to ChatGPT Plus and Enterprise over the next two weeks.

The post said it would be available for other groups “soon after.” It was unclear when it would be added to free versions.

Part of this update may be like Siri and Alexa, where you can ask a question and get the answer.

Anyone who’s used ChatGPT knows its AI isn’t a sterile search engine. It can find patterns and solve complex problems creatively and conversationally.

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According to OpenAI, “Snap a picture of a landmark while traveling and have a live conversation about what’s interesting about it” could expand these abilities. To decide what to make for dinner, take pictures of your fridge and pantry at home and ask questions for a recipe. Take a photo, circle the problem set, and have it share hints with your child after dinner to help them with a math problem.

This development “opens doors to many creative and accessibility-focused applications,” said OpenAI. They added that it will pose “new risks, such as the potential for malicious actors to impersonate public figures or commit fraud.”

The update currently only allows voice chat with AI trained with specific voice actors. It seems you can’t ask, “Read this IFLScience article in the voice of Stephen Hawking.”

However, current AI technology can achieve that.

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Artificial Intelligence

Track People and Read Through Walls with Wi-Fi Signals

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Recent research has shown that your Wi-Fi router’s signals can be used as a sneaky surveillance system to track people and read text through walls.

Recently, Carnegie Mellon University computer scientists developed a deep neural network that digitally maps human bodies using Wi-Fi signals.

It works like radar. Many sensors detect Wi-Fi radio waves reflected around the room by a person walking. This data is processed by a machine learning algorithm to create an accurate image of moving human bodies.

“The results of the study reveal that our model can estimate the dense pose of multiple subjects, with comparable performance to image-based approaches, by utilizing WiFi signals as the only input,” the researchers wrote in a December 2022 pre-print paper.

The team claims this experimental technology is “privacy-preserving” compared to a camera, despite concerns about intrusion. The algorithm can only detect rough body positions, not facial features and appearance, so it could provide a new way to monitor people anonymously.

They write, “This technology may be scaled to monitor the well-being of elder people or just identify suspicious behaviors at home.”

Recent research at the University of California Santa Barbara showed another way Wi-Fi signals can be used to spy through walls. They used similar technology to detect Wi-Fi signals through a building wall and reveal 3D alphabet letters.

WiFi still imagery is difficult due to motionlessness. “We then took a completely different approach to this challenging problem by tracing the edges of the objects,” said UC Santa Barbara electrical and computer engineering professor Yasamin Mostofi.

 

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A futurist predicts human immortality by 2030

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Ray Kurzweil, a computer scientist and futurist, has set specific timelines for humanity’s immortality and AI’s singularity. If his predictions are correct, you can live forever by surviving the next seven years.

Kurzweil correctly predicted in 1990 that a computer would beat human world chess champions by 2000, the rise of portable computers and smartphones, the shift to wireless technology, and the Internet’s explosion before it was obvious.

He even checked his 20-year-old predictions in 2010. He claims that of his 147 1990 predictions for the years leading up to 2010, 115 were “entirely correct” 12 were essentially correct, and 3 were entirely wrong.

Of course, he miscalculates, predicting self-driving cars by 2009.

Though bold (and probably wrong), immortality claims shouldn’t be dismissed out of hand. Kurzweil has made bold predictions like this for years, sticking to his initial dates.

“2029 is the consistent date I have predicted for when an AI will pass a valid Turing test and therefore achieve human levels of intelligence,” Kurzweil said in 2017. “I have set the date 2045 for the ‘Singularity’ which is when we will multiply our effective intelligence a billion fold by merging with the intelligence we have created.”

Kurzweil predicts we will “advance human life expectancy” by “more than a year every year” by 2030. Part of this progress toward the singularity 15 years later will involve nanobots in our bloodstream repairing and connecting our brain to the cloud. When this happens, we can send videos (or emails if you want to think about the duller aspects of being a freaking cyborg) from our brains and backup our memories.

Kurzweil believes the singularity will make humans “godlike” rather than a threat.

We’ll be funnier. Our sexiness will increase. We’ll express love better,” he said in 2015.

“If I want to access 10,000 computers for two seconds, I can do that wirelessly,” he said, “and my cloud computing power multiplies ten thousandfold. We’ll use our neocortex.”

“I’m walking along and Larry Page comes, and I need a clever response, but 300 million modules in my neocortex won’t work. One billion for two seconds. Just like I can multiply my smartphone’s intelligence thousands-fold today, I can access that in the cloud.”

Nanobots can deliver drug payloads into brain tumors, but without significant advances in the next few years, it’s unlikely we’ll get there in seven years. Paralyzed patients can now spell sentences and monkeys can finally play Pong with brain-computer interfaces.

Kurzweil says we’re far from the future, with human-AI interactions mostly the old way. His accuracy will be determined by time. Fortunately, his predictions predict plenty of time.

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