Quest for Awakening Leonard Jacobson ( 88 ).Bill Harris Interviews Ken Wilber on Eckhart Tolle's The Power of Now ( 90 ).Science Says Your Eye Color Reveals A Lot About You ( 101 ).What will you create? How will YOU uplift humanity? Awaken Mind We have an enormous opportunity to use AI for good. In the coming years, it will be the entrepreneurs, creators, and leaders who work withtechnology that will have the most impact. “ By the end of this decade there are going to be two kinds of companies: those that are fully utilizing AI and those that are out of business.” The way I put it, perhaps more bluntly, is: Meanwhile, Elon has announced a new AI company called X.ai to rival OpenAI.Īnd Stability AI itself just released its suite of open-source large language models (LLMs), ranging from 3 billion to 7 billion parameters.Īlphabet CEO Sundar Pichai has said, “Artificial intelligence could have more profound implications for humanity than electricity or fire.” First, Google is creating new AI-powered search tools as part of its project “Magi.” Second, the company is consolidating all of its AI research divisions into Google DeepMind. The company released its own AI-powered chatbot Bard earlier this year, and just last week made two key announcements. Google has been on red alert for months to defend its search business against Microsoft, OpenAI, and others. Bing now has over 100 million daily active users. Microsoft invested $10 billion in OpenAI earlier this year and Bing (remember Bing?) is now AI-powered and disrupting online search. There is no ‘we are still early’ here, trillion-dollar companies are shifting their whole strategy and focus.” “Google and Microsoft are going all-in with generative AI as core to their future. The CEO of Stability AI Emad Mostaque, who I’ve had on my podcast and on the Abundance360 stage, recently made an extraordinary point. Researchers used AlphaFold and the drug discovery platform Pharma.AI to design and synthesize a potential drug to treat hepatocellular carcinoma (HCC), the most common type of primary liver cancer.Īnd so much more (every day)… it’s breathtaking! AI designs a potential cancer drug in 30 days.Auto-GPT, which is based on GPT-4, works through goal-setting, with the AI generating and completing tasks once a given goal has been specified-from creating and completing to-do lists, to ordering food and booking flights. The recently released semi-autonomous AI Auto-GPT removes the need for writing prompts altogether.Microsoft’s AI Vall-E can synthesize your voice using only a 3 second audio sample and preserve intonation, emotion, and voice style. An AI can clone your voice from just 3 seconds of audio.When pitted against over 5,000 human participants, the AI outperformed 45% of expert programmers. DeepMind’s AlphaCode AI outperforms human coders.Soon, our best diagnosticians are going to be AIs. The AI correctly diagnosed 85% in just 18 minutes, compared to top neurologists who achieved 64% accuracy in 50 minutes. An AI system defeats top doctors in tumor diagnosis competition in China.GPT-4, OpenAI’s newest model released last month, then beat us humans by 75% or more on a range of other exams: from the LSAT and the GRE, to the SAT and the AP Math exam.For comparison, the US Medical License Exam normally requires four years of medical school and then a few more years of residency to pass. ChatGPT passes the Bar Exam, US Medical License Exam, and Wharton’s MBA Final Exam.Need more evidence of the power of AI? Below are just a few recent developments, what I call “Proof of AI Domination”: We saw ChatGPT go from 0 to 100 million users in just two months. By 2030, the global AI market is projected to be worth $1.6 trillion. Massive Investments: In 2021, corporations invested $160 billion in AI. Demonetized Training Costs: The cost to train these AI systems has plummeted 99.5% in the last five years. Not only is it a large amount of data, but it is also labeled data, enabling the training of today’s large language models (LLMs). Massive Amount of Labeled Data: Global data has been doubling every two years, and is expected to reach 175 Zettabytes (175 billion-million-megabytes) in 2025. Computational Power: While the power of computation has been doubling every 12 to 24 months for the past 50 years (Moore’s Law), it is just recently (the last 5 years) that there is enough computational power to run today’s deep learning algorithms. There are four reasons that are important to understand: And the first deep-learning-like algorithms were described in 1965.
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