Everyday AI Podcast – An AI and ChatGPT Podcast Everyday AI

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AI + all your data = good move or bad move? Sure, AI can do data crunching wonders when we pair the two together. But, what challenges and conflicts should we be aware of before doing so? Aakash Indurkhya, Head of Product at Virtualitics, joins us to discuss AI and data analysis.

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Join the discussion: Ask Jordan and Aakash questions on AI and data

Related Episodes:
Ep 145: NVIDIA Leader Talks GenAI + Data: Unlocking new ways to interact with our world
Ep 142: AI is Changing Data Analysis: Insider Tips

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn

Topics Covered in This Episode:
1. Generative AI Technology and Data Visualization
2. Role of AI in Data Analysis
3. Statistics Paradox and Data Collection Challenges
4. Importance of Hands-On Experience and Collaboration

Timestamps:
01:30 Daily AI news
04:30 About Aakash and Virtualitics
08:51 Stress of data utilization despite its value.
10:39 Data layers may disagree, causing decision paralysis.
15:33 Generative AI aids human-driven data analytics.
17:38 RAG concept crucial for tracing data decisions.
24:06 Beginning data analysis requires tools, exploration, openness.
26:43 Future of jobs with technology, data and humans.
29:21 Communicate with experts for effective problem-solving.

Keywords:
data in the age of generative AI, large language models, OpenAI model spec, Google DeepMind AlphaFold 3, protein behavior prediction, Zapier Central, AI bots without coding, Virtualisix, data-driven decisions, industry-specific decision intelligence, data abundance paradox, ChatGPT technology, changes in data collection, Apple, Google, maintenance data for HVAC systems, human role in data analysis, industry-specific expertise, generative AI in data visualization, RAG technology, conversational interfaces in generative AI, sensitive data handling, GPT language models, Virtualitix AI platform, decision intelligence apps, data-driven decision paradox, decision congestion, common language in data analysis, data quality, decision socialization.


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Will GenAI be an economic boom? Or cause economic doom? Or maybe something in between? Gad Levanon, Chief Economist at The Burning Glass Institute, joins us to discuss generative AI's impact on the U.S. labor market.

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Related Episodes:
Ep 258: Will AI Take Our Jobs? Our answer might surprise you.
Ep 222: The Dispersion of AI Jobs Across the U.S. – Why it matters

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn

Topics Covered in This Episode:
1. AI's current impact on jobs
2. Generative AI and higher education
3. Skills demand related to generative AI
4. Future for workers and generative AI
5. Generative AI and retirement

Timestamps:
01:30 Daily AI news
04:15 About Gad and The Burning Glass Institute
08:09 Automation and technology impacting labor market trends.
12:13 Generative AI impact on job ads analyzed.
17:27 Employers need specific AI skills for reskilling.
21:28 Concern around AI skills and education needs.
25:06 Generative AI benefits seen in future stock market.
29:37 Generative AI skills essential for future success.

Keywords:
Generative AI, Gad Levanon, AI engines, chatbot infrastructure, computing power, cybersecurity, cloud computing, outsourcing, US colleges, universities, higher education, short-term credentials, computer-related fields, economic shock, stock market, US economy, baby boomers, retirement, layoffs, reskilling, future job market, knowledge worker, US workers, US companies, Blue collar jobs, white collar jobs, online job ads, tech companies, AI automation, Apple, Microsoft, Burning Glass Institute, worker productivity, workforce reduction, new jobs, technological shifts.


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In today's episode, we're diving into the 7 most common mistakes people make while using large language models like ChatGPT. 

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More on this Episode: Episode Page
Join the discussion: Ask Jordan questions on AI

Related Episodes:
Ep 260: A new SORA competitor, NVIDIA’s $700M acquisition – AI News That Matters
Ep 181: New York Times vs. OpenAI – The huge AI implications no one is talking about
Ep 258: Will AI Take Our Jobs? Our answer might surprise you.

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn


Topics Covered in This Episode:
1. Understanding the Evolution of Large Language Models
2. Connectivity: A Major Player in Model Accuracy
3. The Generative Nature of Large Language Models
4. Perfecting the Art of Prompt Engineering
5. The Seven Roadblocks in the Effective Use of Large Language Models
6. Authenticity Assurance in Large Language Model Usage
7. The Future of Large Language Models

Timestamps:
00:00 ChatGPT.com now the focal point for OpenAI.
04:58 Microsoft developing large in-house AI model.
09:07 Models trained with fresh, quality data crucial.
10:30 Daily use of large language models poses risks.
14:59 Free chat GPT has outdated knowledge cutoff.
18:20 Microsoft is the largest by market cap.
21:52 Ensure thorough investigation; models have context limitations.
26:01 Spread, repeat, and earn with simple actions.
29:21 Tokenization, models use context, generative large language models.
33:07 More input means better output, mathematically proven.
36:13 Large language models are essential for business survival.
38:53 Future work: leverage language models, prompt constantly.
40:47 Please rate, share, check out youreverydayai.com.

Keywords:
Large language models, training data, outdated information, knowledge cutoffs, OpenAI's GPT 4, Anthropics Claude Opus, Google's Gemini, free version of Chat GPT, Internet connectivity, generative AI, varying responses, Jordan Wilson, prompt engineering, copy and paste prompts, zero shot prompting, few shot prompting, Microsoft Copilot, Apple's AI chips, OpenAI's search engine, GPT-2 chatbot model, Microsoft's MAI 1, common mistakes with large language models, offline vs online GPT, Google Gemini's outdated information, memory management, context window, unreliable screenshots, public URL verificat
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Is OpenAI launching a search engine this week?
The original worry about Google that lead to the Microsoft-OpenAI partnership.
 Major U.S. newspapers suing Microsoft and Google. 
... And a lot more. This is the AI news that matters for the week of May 6, 2024. 

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More on this Episode: Episode Page
Join the discussion: Ask Jordan questions on AI

Related Episodes:
Ep 260: A new SORA competitor, NVIDIA’s $700M acquisition – AI News That Matters
Ep 181: New York Times vs. OpenAI – The huge AI implications no one is talking about
Ep 258: Will AI Take Our Jobs? Our answer might surprise you.

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn

Topics covered in this episode:



Timestamps:
00:00 OpenAI may announce game-changing chat-integrated search engine.
05:42 OpenAI aims to revolutionize search process.
10:35 Importance of smaller, powerful models for services.
13:01 US newspapers sue OpenAI, Microsoft over copyrighted content
14:40 Large language models scrape Internet data for training, including copyrighted material, raising fair use debate.
17:42 Potential lawsuit between New York Times and OpenAI.
23:08 Microsoft's investment in AI yields significant growth.
26:05 NVIDIA leading in specialized, powerful GPU chips.
29:57 Warren Buffett admits lack of understanding in AI.
33:56 AI's ability to discover new drugs discussed.
36:14 AI news: OpenAI, ChatJPG, EU investigation, $285M allocation.



Topics Covered in This Episode:
1. Investments in Generative AI and Digital Twin Technology
2. The Impact and Potential Threats of AI
3. OpenAI, ChatGPT, and the Upcoming Search Engine
4. Legal Issues Surrounding OpenAI and Microsoft
5. The Evolving Semiconductor Landscape


Keywords:
Jordan Wilson, generative AI, enterprise companies, digital twins, infrastructure improvements, Biden administration, investment, Warren Buffett, AI threats, deep fakes, Eli Lilly, novel drug candidates, OpenAI, ChatGPT, search engine, European Union, Microsoft, semiconductor, Berkshire Hathaway conference, discovering new medicines, Everyday AI podcast, GPT 2 chatbot model, copyright infringement, New York Times, out of court settlement, New York Post, Chicago Tribune, Google's AI dominance, NVIDIA, Sam Altman.
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The much-hyped Humane Ai pin? Dragged through the mud.
The Rabbit R1 AI assistant? Accused of being a box running Android.
Are these devices just too early? Or, do we really not need (or want) AI-powered devices following us everywhere? We'll weigh in with what you need to know.

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More on this Episode: Episode Page
Join the discussion:  Ask Jordan questions on AI-powered devices

Related Episodes:
Ep 201: Apple Vision Pro – The AI-powered product that (hardly) no one needs
EP 184: On-Device AI: What it is and do we need it? What no one’s talking about

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn

Timestamps:
01:50 Daily AI News
06:47 Discussion on need for wearable devices.
08:51 AI devices offer vision and conversation capabilities.
11:21 Wearables can record, take pictures, and assist.
16:48 Ray Bans can have a camera feature.
19:05 Negative reception for major AI gadget launch.
22:37 Using big company's technology to create startups.
24:09 Early AI SaaS companies mimic Apple's marketing.
28:54 Apple designer and generative AI join forces.
30:33 Big tech companies innovate devices, focus on optimization.
34:55 Encourage sharing and community building in AI.

Topics Covered in This Episode:
1. Evaluation of specific AI wearables
2. Concerns and skepticism about AI devices
3. Impact of big tech companies on AI devices
4. Debate about the functionality of AI devices

Keywords:
AI startups, Generative AI, GPU, Large Language Models, Meta, Google, Microsoft, Nvidia, VC, Private equity, AI wearables, Jordan Wilson, Johnny Ivy, Sam Altman, AI Hardware Company, Apple, Samsung, AI-powered devices, AI Pin, Rabbit r one, Ray Ban Meta Glasses, Limitless Pendant, OpenAI's GPT-4 API, Second Brains, Smartphone Integration, Clear lenses Ray-Ban, Humane AI Pin, AI Gadgets, AI Product Reviews, Index GPT


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There's so much uncertainty with AI and what's coming next. How will LLMs and other forms of AI impact our business? What can we do to prepare? Luv Tulsidas, Founder and CEO of Techolution, joins us to discuss how you can secure your business future with AI.

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More on this Episode: Episode Page
Join the discussion:  Ask Jordan and Luv questions on AI

Related Episodes:
Ep 197: 5 Simple Steps to Start Using GenAI at Your Business Today
Ep 238: WWT’s Jim Kavanaugh Gives GenAI Blueprint for Businesses

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn

Timestamps:
01:30 Daily AI news
04:40 About Luv and Techolution
07:00 Shifting business focus to AI
10:49 Businesses seeking clarity on implementing generative AI.
14:35 Companies seek AI for personalized, brand-aligned conversation.
19:00 AI creates disruption, new jobs will emerge.
21:53 AI limited by internet knowledge, lacks human abilities.
25:15 Protecting proprietary AI, monetizing content, avoiding lawsuits.
27:34 Start with successful companies' AI transformation.
32:33 Ethical views vary in different economic systems.
36:00 AI impact on future: Innovation, adapt, bright.
38:44 AI should be done the right way.

Topics Covered in This Episode:
1. Pressure to Adopt AI in Businesses
2. Coping with Uncertain AI Environments
3. AI's Ethical Implications and Perspective on Job Protections
4. Balance and Ethical Consequences of AI Deployment
5. Future Shifts in Job Roles

Keywords:
AI in business, tech boom, practical AI solutions, FOMO in AI, large neural network models, domain-specific training, AI apprenticing, job protection, economic systems, Universal Basic Income, job layoffs, pursuing passions through AI, proprietary AI, Google and AI, data compensation, ethical AI, AI ROI, AI-generated business processes, AI and job losses, securing business future with AI, ad-funded AI chatbots, US government and AI, OpenAI's plans, artificial general intelligence, human jobs and AI, disruption of jobs by AI, problem-solving with AI, data quality in AI, AI and video content, large language models.


Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/