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Generative AI is the technology behind the wave of new online tools used by millions around the world. As the technology is ever more widely deployed, what are its current strengths and its weaknesses?
00:00 – What is generative AI?
00:46 – Breakthroughs and take-up of the technology
02:03 – Strengths
03:32 – Weaknesses
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Don’t fear an AI-induced jobs apocalypse just yet: https://econ.st/3ULbubz
The race of the AI labs heats up: https://econ.st/3MUh1e7
The five best books to understand AI: https://econ.st/3olOX9e
1843: The inventor who fell in love with his AI: https://econ.st/3MUiVeS
Sam Altman, the CEO of ChatGPT creator OpenAI, testified Tuesday before the Senate Judiciary Subcommittee on Privacy, Technology and the Law as the panel examines potential rules for the use of artificial intelligence. New York University professor emeritus Gary Marcus and Christina Montgomery, IBM’s chief privacy and trust officer, also testified at the hearing.
#news #politics #ai
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Hi. In today’s episode, we look at the hype surrounding artificial intelligence, the way corporations are desperate to use it to save money, and the theory among some rich people that it’s going to destroy civilization.
Executive Producer – Katy Stoll
Directed by Will Gordh
Written by Ella Yurman & ChatGPT
Edited by Gregg Meller
Produced by Jonathan Harris
Associate Producer – Quincy Tucker
Post-Production Supervisor – John Conway
Researcher – Marco Siler-Gonzales
Graphics by Clint DeNisco
Head Writer – David Christopher Bell
Narrator – Michael Swaim
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Chapters:
00:00 – Ladies and Gentlemen, Some More News?
02:51 – What Is A.I.?
06:50 – Elon Musk & The Dangers Of A.I.
12:26 – What Is ChatGPT?
20:20 – Okay, but…the apocalypse? Really?
27:12 – What Goes Wrong When A.I. “Creates” Art
35:22 – A.I. Is Already Costing People Their Jobs
41:45 – How A.I. Should Be Regulated To Benefit The Working Class
53:15 – Ladies and Gentlemen, More Some More News
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What is Generative AI and how does it work? What are common applications for Generative AI? Watch this video to learn all about Generative AI, including common applications, model types, and the fundamentals for how to use it.
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With mass layoffs happening in the tech industry and the advent of AI and ChatGPT challenging the need for programmers altogether, many software engineers are in a state of panic, wondering if they should quit coding entirely.
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Discover the amazing new features of ChatGPT-4 openAI chatbot, from image recognition to improved memory, that are pushing the limits of AI chatbot. Find out how GPT4 can solve complex problems and even outperform lawyers. Don’t miss out on this exciting new openAI Chatgpt 4 and see how it compares to older AI chat bot version of GPT3.
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Leak Reveals that OpenAI is developing three revolutionary features for ChatGPT, namely Workspaces, Profiles, and File Uploads. OpenAI’s ChatGPT will enable personalization, multi-domain interaction, and file-based engagement, revolutionizing user experience and redefining AI chatbot technology. Additionally, a business variant of ChatGPT is in the pipeline, set to equip businesses with the power of AI, making ChatGPT an indispensable, game-changing tool in the realm of AI technology led by Sam Altman.
#chatgpt #openai #gpt4
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These videos are for entertainment purposes only and they are just Shane’s opinion based off of his own life experience and the research that he’s done. Shane is not an attorney, CPA, insurance, or financial advisor and the information presented shall not be construed as tax, legal, insurance, safety or financial advice. If stocks or companies are mentioned, Shane might have an ownership interest in them. Affiliate links may be present, the offers and numbers presented may change over time so please make sure to confirm that the offer is still valid. Some offers mentioned may no longer be available or they have been changed. Please don’t make buying or selling decisions based on Shane’s videos. If you need such advice, please contact the qualified legal or financial professionals, don’t just trust the opinion of a stranger on the internet and always make sure to do your own research and enjoy this family friendly content.
Sources and further readings for jobs and college degrees:
bls.gov(bureau of labor statistics)
nces.ed.gov(national center for educational statistics)
payscale(provides information on jobs and degrees)
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ChatGPT is now the fastest-growing consumer app in human history. Problem is, almost no one knows how it actually works. This is everything you need to know.
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When many Americans think of artificial intelligence, they think of devices like Siri or Alexa. But that’s so 2010, Glenn explains. In fact, AI is FAR beyond those capabilities, and it’s learning more skills each day — some of which truly are terrifying to imagine. In this clip, Glenn recaps a recent conversation he had with Tristan Harris, a former design ethicist at Google. Glenn explains that we’re now in ‘second contact’ with A.I., and how A.I. is learning to MANIPULATE us just like fellow humans can…
You can watch the entire conversation Glenn recently had with Tristan about this topic, here:
https://www.youtube.com/watch?v=VMAUfwxSGi8
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Learn Data Science Tutorial - Full Course for Beginners
Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the “sexiest job of the 21st century.” You’ll learn the important elements of data science. You’ll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You’ll have a solid foundation for future learning and applications in your work. With data science, you can do what you want to do, and do it better. This course covers the foundations of data science, data sourcing, coding, mathematics, and statistics.
💻 Course created by Barton Poulson from datalab.cc.
🔗 Check out the datalab.cc YouTube channel: https://www.youtube.com/user/datalabcc
🔗 Watch more free data science courses at http://datalab.cc/
⭐️ Course Contents ⭐️
⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science
– Welcome (1.1)
– Demand for Data Science (2.1)
– The Data Science Venn Diagram (2.2)
– The Data Science Pathway (2.3)
– Roles in Data Science (2.4)
– Teams in Data Science (2.5)
– Big Data (3.1)
– Coding (3.2)
– Statistics (3.3)
– Business Intelligence (3.4)
– Do No Harm (4.1)
– Methods Overview (5.1)
– Sourcing Overview (5.2)
– Coding Overview (5.3)
– Math Overview (5.4)
– Statistics Overview (5.5)
– Machine Learning Overview (5.6)
– Interpretability (6.1)
– Actionable Insights (6.2)
– Presentation Graphics (6.3)
– Reproducible Research (6.4)
– Next Steps (7.1)
⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:46)
– Welcome (1.1)
– Metrics (2.1)
– Accuracy (2.2)
– Social Context of Measurement (2.3)
– Existing Data (3.1)
– APIs (3.2)
– Scraping (3.3)
– New Data (4.1)
– Interviews (4.2)
– Surveys (4.3)
– Card Sorting (4.4)
– Lab Experiments (4.5)
– A/B Testing (4.6)
– Next Steps (5.1)
⌨️ Part 3: Coding (2:32:42)
– Welcome (1.1)
– Spreadsheets (2.1)
– Tableau Public (2.2)
– SPSS (2.3)
– JASP (2.4)
– Other Software (2.5)
– HTML (3.1)
– XML (3.2)
– JSON (3.3)
– R (4.1)
– Python (4.2)
– SQL (4.3)
– C, C++, & Java (4.4)
– Bash (4.5)
– Regex (5.1)
– Next Steps (6.1)
⌨️ Part 4: Mathematics (4:01:09)
– Welcome (1.1)
– Elementary Algebra (2.1)
– Linear Algebra (2.2)
– Systems of Linear Equations (2.3)
– Calculus (2.4)
– Calculus & Optimization (2.5)
– Big O (3.1)
– Probability (3.2)
⌨️ Part 5: Statistics (4:44:03)
– Welcome (1.1)
– Exploration Overview (2.1)
– Exploratory Graphics (2.2)
– Exploratory Statistics (2.3)
– Descriptive Statistics (2.4)
– Inferential Statistics (3.1)
– Hypothesis Testing (3.2)
– Estimation (3.3)
– Estimators (4.1)
– Measures of Fit (4.2)
– Feature Selection (4.3)
– Problems in Modeling (4.4)
– Model Validation (4.5)
– DIY (4.6)
– Next Step (5.1)
—
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