Think AI is hitting a wall? Nope.

This is just the start. Actually, we're at the first chapter. Here's what that means, and how you can move your company ahead.

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Topics Covered in This Episode:

1. Generative AI's current phase
2. Meta's in-house AI chips development
3. OpenAI's new developer tools
4. Day zero of AI and future prospects
5. Reinforcement learning advancements
6. Emergent reasoning capabilities in AI
7. Business implications of AI advancements
8. AI in healthcare and science

Timestamps:
00:00 Day Zero of AI

03:31 AI Tools Enhance Customization & Access

09:02 Reinforcement Learning Enhances AI Reasoning

11:27 Agentic AI: The Future of Tasks

15:59 Tech Potential vs. Everyday Utilization

18:48 AI Models Offer Broad Benefits

23:15 "Generative AI: Optimism and Oversight"

27:08 Generative AI vs. Domain-Specific AI

29:24 Superhuman AI: Next Frontier

Keywords:
Generative AI, Fortune 100 leaders, chat GBT, Microsoft Copilot, enterprise companies, day zero of AI, livestream podcast, free daily newsletter, leveraging AI, capital expenditures, Meta AI chips, Nvidia, Taiwan's TSMC, AI infrastructure investments, Amazon, Google, Microsoft, OpenAI, responses API, agents SDK, legal research, customer support, deep research, agentic AI, supervised learning, reinforcement learning, language models, health care, computational biology, AlphaFold, protein folding prediction.

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Blink, and you’ve already missed like 7 AI updates.

The large language models we use and rely on? They’re change out more than your undies.

(No judgement here.)

But real talk — businesses have made LLMs a cornerstone of their business operations, yet don’t follow the updates.

Don’t worry shorties. We’ve got ya.

In our first ever LLM Monthly roundup, we’re telling you what’s new and noteworthy in your favorite LLMs.

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Topics Covered in This Episode:

1. ChatGPT 4.1 New Features Overview
2. ChatGPT Shopping Platform Launch
3. ChatGPT's Microsoft SharePoint Integration
4. ChatGPT Memory and Conversation History
5. Google Gemini 2.5 Pro Updates
6. Gemini Canvas Powerful Applications
7. Claude Integrations with Google Workspace
8. Microsoft Copilot Deep Research Insights
   
   

Timestamps:
00:00 Saudi Arabia's $600B AI Investment

06:44 Monthly AI Model Update Show

08:11 OpenAI Launches GPT-4.1 Publicly

11:52 AI Research Tools Comparison

16:29 Perplexity's Pushy Shopping Propensity

19:55 ChatGPT Memory: Pros and Cons

22:29 Gemini Canvas vs. OpenAI Canvas

25:06 AI Model Competition Highlights

28:25 Google Gemini Rivals OpenAI's Research

32:30 "Claude's Features and Limitations"

37:05 Anthropic's Educational AI Innovation

39:02 Exploring Copilot Vision Expansion

41:38 Meta AI Launch and Llama 4 Models

46:27 "New iOS Voice Assistant Features"

47:54 "Enhancing iOS Assistant Potential"

Keywords:
ChatGPT, AI updates, Large Language Model updates, OpenAI, GPT 4.1, GPT 4.0, GPT 4.5, GPT 4.1 Mini, Saudi Arabia AI investment, NVIDIA Blackwell AI chips, AMD deal, Humane startup, Data Vault, AI data centers, Logic errors moderation, Grox AI, Elon Musk, XAI, Google Gemini, ChatGPT shopping, Microsoft SharePoint integration, OneDrive integration, deep research, AI shopping platform, Google DeepMind, Alpha Evolve, evolutionary techniques, AI coding, Claude, Anthropic Claude, Confluence integration, Jira integration, Zapier integration, ChatGPT enterprise, API updates, Copilot pages, Microsoft three sixty five, Bing search, Meta AI, Llama 4, Llama 4 Maverick, Llama 4 Scout, Perplexity, voice assistant, Siri alternatives, Grok Studio, AI social network.

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AI is shaking up qualitative research: speeding things up, cleaning messy transcripts, and even identifying hidden patterns.

Sounds amazing, right?

Buuuuuuuut there’s a catch.

When does AI go from helpful assistant to heavy-handed editor, scrubbing out the human insights qualitative research was built on?

In this episode of Everyday AI, we're tackling how to balance AI-powered qualitative research without losing touch with human nuance.

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Topics Covered in This Episode:

1. Importance of Qualitative Research Training
2. Challenges in AI-Assisted Qualitative Research
3. AI's Role in Data Transcription
4. Human-Led Analysis in Qualitative Research
5. AI's Impact on Data Accessibility
6. Limitations of AI in Qualitative Analysis
7. Future of AI and Qualitative Research
8. Critical Thinking in AI-Assisted Research

Timestamps:
00:00 PhD and Qualitative Research Training

05:07 "Qualitative Research and Multiple Narratives"

08:04 AI in Research: Balancing Automation

09:57 AI-Assisted Data Analysis Caution

16:23 AI's Impact on Qualitative Research

19:19 Analyzing Qualitative Data Interpretation

25:11 Balancing AI in Qualitative Research

Keywords:
Qualitative research, qualitative researcher, AI use in research, AI in qualitative research, AI-informed, human-led, thoughtful AI use, research impacts, health psychology, apprentice plumber analogy, training for PhD students, data analysis, transcribing interviews, transcription time, structured versus unstructured data, meaning making, words as data, interpretive work, subjective interpretation, data set analysis, line by line coding, thematic analysis, story telling in research, ensuring rigor in research, critical thinking in research, efficiency in research processes, literature gap identification, data visualization, AI as an intern, sharing research findings with lay audience, implicit meaning in data, biases in models, accessibility of academic work, academic pressure to publish, research dissemination, insights from research, qualitative research processes, interpretation in qualitative research.

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Agentic AI is equally as daunting as it is dynamic. So…… how do you not screw it up?

After all, the more robust and complex agentic AI becomes, the more room there is for error.

Luckily, we’ve got Dr. Maryam Ashoori to guide our agentic ways.

Maryam is the Senior Director of Product Management of watsonx at IBM. She joined us at IBM Think 2025 to break down agentic AI done right.

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Topics Covered in This Episode:

1. Agentic AI Benefits for Enterprises
2. Watson X's New Features & Announcements
3. AI-Powered Enterprise Solutions at IBM
4. Responsible Implementation of Agentic AI
5. LLMs in Enterprise Cost Optimization
6. Deployment and Scalability Enhancements
7. AI's Impact on Developer Productivity
8. Problem-Solving with Agentic AI

Timestamps:
00:00 AI Agents: A Business Imperative

06:14 "Optimizing Enterprise Agent Strategy"

09:15 Enterprise Leaders' AI Mindset Shift

09:58 Focus on Problem-Solving with Technology

13:34 "Boost Business with LLMs"

16:48 "Understanding and Managing AI Risks"

Keywords:
Agentic AI, AI agents, Agent lifecycle, LLMs taking actions, WatsonX.ai, Product management, IBM Think conference, Business leaders, Enterprise productivity, WatsonX platform, Custom AI solutions, Environmental Intelligence Suite, Granite Code models, AI-powered code assistant, Customer challenges, Responsible AI implementation, Transparency and traceability, Observability, Optimization, Larger compute, Cost performance optimization, Chain of thought reasoning, Inference time scaling, Deployment service, Scalability of enterprise, Access control, Security requirements, Non-technical users, AI-assisted coding, Developer time-saving, Function calling, Tool calling, Enterprise data integration, Solving enterprise problems, Responsible implementation, Human in the loop, Automation, IBM savings, Risk assessment, Empowering workforce.

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OpenAI is making moves to go public. Apple and Anthropic are teaming up for vibe coding. And Google is quietly continuing its dominance with a quiet update to the world's most powerful AI model.

Once again, the big names are shaking up the AI space.

Don't burn hours a day trying to keep up. Spend your Mondays with Everyday AI and our weekly 'AI News that Matters' segment.

You'll be the smartest person in AI at your company.

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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. Anthropic and Apple AI Partnership
2. Apple AI Coding with Anthropic's Claude
3. OpenAI's Wind Surf Acquisition
4. AI Search Engines in Apple's Safari
5. OpenAI and FDA Drug Approval Talks
6. Google Gemini 2.5 Pro IO Edition
7. Amazon AI Coding Tool Kiro
8. OpenAI's Nonprofit Control Decision

Timestamps:
00:00 "Everyday AI: Podcast and Newsletter"

03:44 Apple Eyes External AI Partnerships

07:12 OpenAI's Wind Surf Acquisition Disrupts Coding

10:28 Windsurf Model Selection and Future

14:24 Apple's AI Search Engine Shift

20:45 FDA-OpenAI AI Drug Approval Talks

22:50 AI Literacy Challenges

27:14 "Gemini 2.5 Pro Unveiled"

31:27 Advanced AI Coding Tools Emerging

34:50 OpenAI Governance and Structure Shift

36:50 OpenAI-Microsoft Partnership Revamp Talks

42:40 Tech Giants Shake Up AI Landscape

Keywords:
Anthropic, Apple, Vibe coding, Google Gemini, 2.5 pro IO edition, OpenAI, Microsoft partnership, IPO, Artificial General Intelligence, AI coding models, Claude SONNET, Swift Assist, Anthropic's Claude, Wind Surf, $3 billion acquisition, AI IDE, Race car driver analogy, AI search engines, Safari, Perplexity AI, ChatGPT, Search engine market, FDA, Drug approval process, AI-assisted scientific review, Google IO edition, Web dev arena leaderboard, Amazon Web Services, AI-powered code generation, Kiro, Multimodal capabilities, OpenAI nonprofit arm, Public Benefits Corporation, Equity stake, Microsoft partnership renegotiation, $13 billion investment, SoftBank, Oracle, Stargate project

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Still experimenting with AI?

Cool.

While you tinker with prompts and pilot projects, real businesses are stacking wins—and actual revenue.

They’re not chasing shiny tools.
They’re building unfair advantages.
They’re automating what matters and scaling faster than their competition can.

And no, it’s not just Big Tech.

It’s manufacturers. Retailers. Healthcare companies. Real people solving real problems—with AI that works today.

You’ve got two options:
🛑 Stay stuck in “research mode”
✅ Or see how the pros are doing it and steal their playbook

Ajay Malik—former Google exec and CEO of StudioX—joins us to share how real businesses are crushing it right now with AI.

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Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
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Topics Covered in This Episode:

1. Role of AI in Business Competition
2. Studio X's AI Platform for Businesses
3. Challenges Businesses Face with AI Adoption
4. Real Applications for Top Line Growth with AI
5. Improving Products with Predictive Features
6. Increasing Bottom Line with Operational Efficiency
7. AI's Role in Automating Repetitive Tasks
8. Enhancing Business Operations through AI
9. AI Steering Committees for Continuous Evaluation
10. Specific Metrics for AI Success in Companies

Timestamps:
00:00 AI Surpasses Turing Test

03:48 AI Milestones and Product Updates

09:54 AI-Driven Revenue Strategies

10:38 AI Enhancing Product Usability

14:36 Automate Repetitive Tasks

17:33 "Unlearning Manual Task Habits"

22:45 Maximize Productivity with AI

26:40 Embracing AI's Rapid Business Shift

27:44 "Identify Business Pain Points Together"

31:09 Leading With AI in Business

Keywords:
Generative AI, Large Language Models, Enterprise companies, Smaller businesses, Increase top line revenue, Increase bottom line efficiency, Real businesses, AI platform, AI adoption, ROI versus hype, Supply chain management, Predictive analytics, AI voice control, Embedded inspection, Retain customers, Operational efficiency, Repetitive tasks, Automated processes, Google, Skill differentiation, AI assistant, AI augmenter, AI-enabled products, Sales opportunities, Knowledge management, Error reduction, Demand forecast, Course correction, Steering committee, Business metrics, Lead generation, AI use cases, Measurable applications, Think big, Scale fast.

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Maybe we should just skip the whole AGI thing?

And instead focus on something ..... useful?

Ruchir Puri thinks that's the way forward.

Ruchir, IBM Research & IBM Fellow, knows a thing or two about AI and how to make it useful.

For decades, he's helped develop the world's biggest AI breakthroughs, like IBM Watson.

Don't miss this convo if you're ready to make AI a bit more useful.

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More on this Episode: Episode Page
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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. Allocation of AGI Focus vs. AUI (Artificial Useful Intelligence)
2. Ruchir Puri’s Background in Automation and AI at IBM
3. Discussion of AGI’s Unclear Definition and Historical Milestones (Deep Blue and Watson)
4. Breakdown of Intelligence into IQ, EQ, and RQ
5. Emphasis on AUI’s Practical Uses in Daily Life and Business
6. Evolution of Human Work Due to AI Advancements
7. IBM's Software Engineering Agent for Developer Productivity
8. Importance of Feedback Systems and Intelligent Agents
9. Steps for Business Leaders: Education, Strategy, and Skill Development

Timestamps:
00:00 Everyday AI Podcast & Newsletter

03:57 Debating AGI and Scaremongering

09:31 Evolution of Knowledge Work

10:47 Seamless Language Generation's Impact

13:57 AI's Growing Reasoning Abilities

19:18 "Software's Dominance and Developer Focus"

22:22 AI Solutions for Cybersecurity Challenges

26:40 ChatGPT Struggles with Math

29:32 Preparing Human Skills for AI's Rise

30:35 "Embrace and Strategize with AI"

34:00 "Subscribe for Daily AI Insights"

Keywords:
artificial intelligence, AI podcast, large language models, LLMs, artificial general intelligence, AGI, artificial useful intelligence, AUI, IBM, AI in business, AI strategy, AI implementation, machine learning, deep blue, jeopardy, Watson, Granite models, reasoning AI, agentic AI, AI in software development, AI tools, AI automation, generative AI, EQ, RQ, IQ, AI reasoning, AI technology, AI in careers, AI and human skills, AI in enterprises.

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One of the biggest downsides of consumer AI?

It doesn't have up-to-date access to your enterprise data.

Even as frontier labs work tirelessly to connect and integrate AI chatbots with your data, we're a far way off from that happening.

Unless you're using a platform like IBM's watsonx. And if you are using watsonx, your go-to enterprise AI platform just got a TON more powerful.

IBM just unveiled updates across its watson ecosystem at its Think 2025 conference. We've been here covering every step of it, so we're jumping into what you need to know.

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More on this Episode: Episode Page
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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. IBM Think Conference 2025 Highlights
2. IBM's Watson AI Platform Updates
3. Enterprise Workflow with Watson x Orchestrate
4. Build Your Own AI Agents Features
5. Prebuilt Domain Agents Overview
6. New Agent Catalog with 50+ Agents
7. IBM and Salesforce AI Collaboration
8. IBM's Partnership with Oracle for AI

Timestamps:
00:00 Amazon's Advanced AI Coding Tool Kiro

03:52 AI Delivers Victim's Court Statement

07:12 "IBM Conference Insights and Updates"

12:52 Rise of Small Language Models

16:03 Watson x Orchestrate Overview

17:13 "Streamlined Internal Workflow Automation"

21:02 DIY AI Agents Revolution

23:52 AI Trust Through Transparent Reasoning

28:23 Prebuilt AI Agents Boost Efficiency

31:20 IBM Watson AI Traceability Insights

35:14 AI Platforms Crossover: Watson and Salesforce

41:10 IBM's AI Data Platform Enhancement

44:59 IBM Watson x Q&A Invitation

Keywords:
IBM Think 2025, AI updates, Enterprise work, IBM Watson, Generative AI, Enterprise organizations, IBM products, Watson AI platforms, AI news, Amazon Kiro, Code generation tool, AI agents, Technical design documents, OpenAI, Google's Gemini 2.5 Pro, Web app development, Large Language Models, Enterprise systems, Dynamic enterprise data, Enterprise-grade versions, Meta's Llama, Mistral models, Granate models, Small language models, IBM Watson x, AI agent creation, Build your own agents, Prebuilt domain agents, Salesforce collaboration, Oracle Cloud, Multi agent orchestration, Watson x data intelligence, Unstructured data, Open source models, Consumer grade GPU, Data governance, Code transformation, Semantic understanding, Hybrid cloud strategy.

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