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As more people discover ChatGPT’s artificial intelligence, KARE 11’s Chris Hrapsky checks out its capabilities and limitations, and gets some surprising responses.
Chris also digs deeper into AI technology, how it works, and the potential concerns that go along with it here: https://www.youtube.com/watch?v=fs3NhePN2Mg
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I just came across a long lost clip of Charlie Munger explaining the three things he would do to generate 50% annual returns investing small amounts of money. This clip looks like it was shot on an iPhone 4 but it is Munger at his absolute best. If you want to build real wealth, you need to see it. There is an old saying that it “takes money to make money”. This saying may be true, but the amount of money you need to get started generating high returns is not as much as many would believe, according to Munger.
Charlie Munger is the Vice President of Berkshire Hathaway and Warren Buffett’s business partner. There are three important principles you need to understand if you want to follow Munger’s advice on generating high returns on small sums of money.
The first principle is “Look in the inefficient markets”. Munger is the Vice Chairman of Berkshire Hathaway. As of the making of this video, Berkshire has a market cap approaching 0 billion. That makes Berkshire the 9th largest company in the world by market cap and the biggest non-tech, US based company in the world.
To most people, Berkshire’s massive size would seem like a huge advantage when it comes to investing, right? Well, actually, that’s not the case. Charlie and Warren have repeatedly said that Berkshire’s size is an impediment to generating high investment returns. Because Berkshire has so much money, Warren and Charlie are forced to only focus on large investment opportunities. The odds of these large investment opportunities being mispriced, or to use an investing term, inefficient, are extremely low.
*Disclaimer: Neither this video, not any content produced on this channel should ever be considered investing advice or official financial advice. All content is made for entertainment and educational purposes.
The scandal surrounding OpenAI and Sam Altman continues to make waves. A recent report from Reuters, citing insider information, has brought a new twist to the story. Allegedly, several staff researchers at OpenAI have written a letter to the board of directors, raising concerns about a groundbreaking discovery in the field of AI that they believe could pose a threat to humanity.
Sources describe this letter as the final straw for the board, who have already had numerous grievances against Altman. These concerns include worries about the premature commercialization of OpenAI’s advancements without fully understanding the implications of disseminating such technologies.
0:00 Beginning
0:35 Altman, OpenAI, GPT-5 and superintelligent AI
3:50 Starship’s second flight
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8:06 Cruise robotaxi problems
9:32 Unique Transformer Drone
10:51 3D Printing a robotic arm
11:54 Superplane for DARPA
13:19 Google DeepMind unveils new AI
14:24 Mass production of humanoid robots
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Upon receiving this information, Reuters reached out to OpenAI for comment, but the company declined to respond. However, insiders revealed that employees received an internal message, supposedly confirming the existence of a project called Q-Star, from Mira Muratti. Some within OpenAI believe that Q-Star could be a game-changing breakthrough in the development of general artificial intelligence.
Following the Reuters publication, OpenAI spokesperson Lindsay Held Bolton distanced herself from Q-Star, stating to The Verge, “Mira informed employees about the media reports, but did not comment on the accuracy of the information.”
Did this satisfy the media and the public? Not at all! The general consensus, both online and offline, is that OpenAI employees have stumbled upon something that suggests the imminent emergence of general AI. This discovery has greatly excited Sam Altman while simultaneously alarming the board of directors, leading to attempts to remove Altman from his position and halt this work. However, luck was not on their side, as Q-Star prevailed in this round.
So what do we know about Q-Star? As we previously reported, this AI model has demonstrated an ability to solve math problems like a human. Recent details have emerged, indicating that the model has learned to solve math problems without any explicit training. Although currently at the level of elementary school students, this achievement is significant. When prompted with text queries, the generative AI utilizes statistical analysis, resulting in potentially varying answers with each interaction. The ability to solve mathematical problems without errors brings the AI closer to human intelligence, showcasing its potential for generalization, learning, and understanding.
Researchers believe that mathematics represents the cutting edge of generative AI development. At its core, problem-solving is the ability to discern truth from falsehood. This has remained a fundamental barrier for current versions of GPT. Overcoming this barrier implies the capacity for self-learning and self-development based on self-generated data.
Is it true or not? We firmly believe that general AI is the undeniable elephant in the room. Therefore, we eagerly await further statements from Sam Altman, who has managed to retain his position as OpenAI’s director, as well as the unwavering loyalty of the company’s employees and their collective faith in the possibility of creating a shared artificial intelligence for the betterment of humankind.
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Pro Robots is not just a channel about robots and future technologies, we are interested in science, technology, new technologies and robotics in all manifestations, science news, technology news, science and technology news, so in the future it is possible to expand the topics for issues. For today our vlog just tells about complicated things, follows the news, makes reviews of exhibitions, conferences and events where the main actors are robots! Subscribe to the channel and give the video a like!
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This video on “What is Artificial Intelligence” will give you a brief overview of artificial intelligence as a technology in just 5 minutes. We will start with a minor introduction to artificial intelligence in which we will know what is artificial intelligence with the help of examples. Moving ahead we will see what are the uses of AI, what is strong AI and what is weak AI. We will warp up this video by making you understand the major difference between AI ML and Deep Learning which will be followed by the future scope of artificial intelligence.
00:00 What is AI?
00:37 Uses of AI (Artificial Intelligence)
01:48 What is AI (Artificial Intelligence)
02:02 Weak AI (Artificial Intelligence)
02:18 Strong AI (Artificial Intelligence)
03:13 Difference between AI ML and Deep learning
05:00 Future of Artificial Intelligence
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What is Artificial Intelligence?
Artificial Intelligence or AI is the combination of algorithms used for the purpose of creating intelligent machines that have the same skills as a human being. It uses machine learning and deep learning techniques to build complex systems.
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