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Category: information science – Page 104

A key algorithm that quietly empowers and simplifies our electronics is the Fourier transform, which turns the graph of a signal varying in time into a graph that describes it in terms of its frequencies.

Packaging signals that represent sounds or images in terms of their frequencies allows us to analyze and adjust sound and image files, Richard Stern, professor of electrical and computer engineering at Carnegie Mellon University, tells Popular Mechanics. This mathematical operation also makes it possible for us to store data efficiently.

The invention of color TV is a great example of this, Stern explains. In the 1950s, television was just black and white. Engineers at RCA developed color television, and used Fourier transforms to simplify the data transmission so that the industry could introduce color without tripling the demands on the channels by adding data for red, green, and blue light. Viewers with black-and-white TVs could continue to see the same images as they saw before, while viewers with color TVs could now see the images in color.

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https://youtube.com/watch?v=PB6TTzoYLQY&feature=share

Future computers You WON’T See Coming…(analog computing)

An emerging technology called analogue AI accelerators has the potential to completely change the AI sector. These accelerators execute computations using analogue circuits, which are distinct from digital circuits. They have advantages in handling specific kinds of AI algorithms, speed, and energy efficiency. We will examine the potential of this technology, its present constraints, and the use of analogue computing in AI in the future. Join us as we explore the realm of analogue AI accelerators and see how they’re influencing computing’s future. Don’t miss this engaging and educational film; click the subscribe button and check back for additional information about the newest developments in AI technology.

#ai #computing #technology.

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Architects urgently need to get to grips with the existential threat posed by AI or risk, in ChatGPT’s words, “sleepwalking into oblivion”, writes Neil Leach.

In the near future, architects may become a thing of the past. Artificial intelligence (AI) is quickly advancing to a point where it can generate the design of a building completely autonomously. With the potential to create designs faster and with more accuracy than ever before, AI has the potential to revolutionize the architecture industry, leaving traditional architects out of the equation. This could spell the end of the profession as we know it, raising questions of what the future holds for architects in a world of AI-generated buildings.

I did not write the paragraph above. It was generated by ChatGPT, a highly impressive AI text generator that recently launched. Make no mistake: despite its innocuous-sounding name, ChatGPT is no simple chat bot. It is based on GPT3, a massive Generative Pre-Trained Transformer (GPT) that uses Deep Learning to produce human-like text from user-inputted prompts.

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Dr. Craig Kaplan discusses Artificial Intelligence — the past, present, and future. He explains how the history of AI, in particular the evolution of machine learning, holds the key to understanding the future of AI. Dr. Kaplan believes we are on an inexorable path towards Artificial General Intelligence (AGI) which is both an existential threat to humanity AND an unprecedented opportunity to solve climate change, povery, disease and other challenges. He explains the likely paths that will lead to AGI and what all of us can do NOW to increase the chances of a positive future.

Chapters.
0:00 Intro.
0:22 Overiew & summary.
0:45 Antecedents of AI
1:15 1956: Birth of the field / Dartmouth conference.
1:33 1956: The Logic Theorist.
1:58 1986: Backprogation algorithm.
2:26 2016: SuperIntelligent AI / Alpha Go.
2:51 Lessons from the past.
3:59 Today’s “Idiot Savant” AI
4:45 Narrow vs. General AI (AGI)
5:15 Deep Mind’s Alpha Zero.
6:19 Demis Hassabis on Alpha Fold.
6:47 Alpha Fold’s amazing performance.
8:03 OpenAI’s ChatGPT
9:16 OpenAI’s DALL-E2
9:50 The future of AI
10:00 AGI is not a tool.
10:30 AGI: Intelligent entity.
10:48 Humans will not be in control.
11:16 The alignment problem.
11:45 Alignment problem is unsolved!
12:45 Likely paths to AGI
13:00 Augmented Reality path to AGI
13:26 Metaverse / Omniverse path to AGI
14:20 AGI: Threat AND Opportunity.
15:10 Get educated — books.
15:48 Get educated — videos.
16:20 Raise awareness.
16:44 How to influence values of AGI
17:52 No guarantees, we must do what we can.
18:47 AGI will learn our values.
19:30 Wrap up / contact info.

LINKS & REFERENCES
Contact:
@iqcompanies.
[email protected].

Websites.

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Did We Find Them? 8 Candidate Alien Signals Found with a new AI Algorithm by SETI.

A deep-learning search for technosignatures of 820 nearby stars.
https://seti.berkeley.edu/ml_gbt/MLSETI_NatAstron_arxiv3.pdf.

YouTube Membership: https://www.youtube.com/channel/UCz3qvETKooktNgCvvheuQDw/join.
Podcast: https://anchor.fm/john-michael-godier/subscribe.
Apple: https://apple.co/3CS7rjT

More JMG

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Google worked to reassure investors and analysts on Thursday during its quarterly earnings call that it’s still a leader in developing AI. The company’s Q4 2022 results were highly anticipated as investors and the tech industry awaited Google’s response to the popularity of OpenAI’s ChatGPT, which has the potential to threaten its core business.

During the call, Google CEO Sundar Pichai talked about the company’s plans to make AI-based large language models (LLMs) like LaMDA available in the coming weeks and months. Pichai said users will soon be able to use large language models as a companion to search. An LLM, like ChatGPT, is a deep learning algorithm that can recognize, summarize and generate text and other content based on knowledge from enormous amounts of text data. Pichai said the models that users will soon be able to use are particularly good for composing, constructing and summarizing.

“Now that we can integrate more direct LLM-type experiences in Search, I think it will help us expand and serve new types of use cases, generative use cases,” Pichai said. “And so, I think I see this as a chance to rethink and reimagine and drive Search to solve more use cases for our users as well. It’s early days, but you will see us be bold, put things out, get feedback and iterate and make things better.”

Pichai’s comments about the possible ChatGPT rival come as a report revealed this week that Microsoft is working to incorporate a faster version of ChatGPT, known as GPT-4, into Bing, in a move that would make its search engine, which today has only a sliver of search market share, more competitive with Google. The popularity of ChatGPT has seen Google reportedly turning to co-founders Larry Page and Sergey Brin for help in combating the potential threat. The New York Times recently reported that Page and Brin had several meetings with executives to strategize about the company’s AI plans.

During the call, Pichai warned investors and analysts that the technology will need to scale slowly and that he sees large language usage as still being in its “early days.” He also said that the company is developing AI with a deep sense of responsibility and that it’s going to be careful when launching AI-based products, as the company plans to initially launch beta features and then slowly scale up from there.

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The rise of social media has changed our day to day lives. But more and more reports show that social media and especially social media can impact our brain. Social media addiction might also to a decline in mental health. How does social media changes us? And are the effects by social media addiction reversal?

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Social media has been developed to connect people. However, quite early, scientists found that social media (and social media addiction) can lead to changes in the brain such an enlarged amygdala. First reports surfaced showing that people compare their lives to lives they see on social media and report a decline of mental health upon heavy social media use. It seems like our brains cannot distinguish between social media and the real world. Social media also led to an attention span crisis meaning that we have a harder time to focus if we spend much time on social media. Moreover, social media is able to feed into the reward system of our brains. Everytime we perceive something good dopamine producing cells in the brain release dopamine which leads to a good feeling. Social media has used this mechanism to provide us with a constant stream of good feelings. Social media algorithms have been optimize to show more social media content in a shorter period of time leading to more dopamine. As a result, some argue that social media addiction should be recognized as a mental disorder.

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