Episode 049: All Things AI - Big Data Broke the AI Winter

Topics covered in this episode include… 

- AI in analytics analysis: Using AI for data interpretation, trend spotting and predictions. 

- AI for business administration: Future productivity tools leveraging AI for tasks like calendar and inbox management. 

- Utilising AI for meetings and file management: Integration of AI tools like Otter.ai for minute taking, action point extraction, and efficient digital file organisation. 

- AI in customer support: AI-based customer service tools for sentiment analysis, support requests, documentation, and communication trend insights. 

- Content creation with AI: AI application in repurposing content, drafting emails, creating captions, and blog post outlining. 

- AI in product development: AI assistance in concept creation, product design, development, code writing and technical troubleshooting.

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Topics covered in this episode include… 

- Explanation of AI: Described as predictive text on steroids, trained with massive amounts of data.

- AI's training: Discussion on AI tools being trained on existing public content on the internet.

- Issue of bias in AI: Brief mention of how word probability can lead to biassed results in AI-generated content.

- Intellectual property and AI: Conversation on who owns copyright when content is created using AI.

- OpenAI's stance on copyright: Information on OpenAI's policy that users retain copyright for outputs generated using their models.

- Importance of AI/plagiarism checker: Recommendation to use an AI/plagiarism checker before publishing AI-generated content online.

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Topics covered in this episode include… 

- AI goldrush and overfunding in Silicon Valley

- OpenAI's ChatGPT: Free and $20/month versions, user data usage

- Microsoft's $11 billion investment in OpenAI: Threat to Google's market dominance

- Anthropic: OpenAI competitor, creator of "generative" language model, Claude

- Google and Meta's AI forays: Google's Bard and Meta's open-source Llama2

- Europe's lag in large language model development: Cautious data privacy approach, LEAM.ai's open-source initiative.

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Topics covered in this episode include… 

- Understanding Artificial Intelligence: AI's capability to display human-like intelligence.

- Breaking down AI Algorithms: Step-by-step rules that guide computers.

- Natural Language Processing: How machines understand and generate human language.

- The concept of Machine Learning: Computers learning from data without specific programming.

- Introduction to Neural Networks: Simulating human learning in computing systems.

- Decoding Data Mining: Discovering patterns and relationships in large datasets.

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We’re exploring where AI came from, how it was built, and what it is in this series of short and snappy episodes that give you a jargon-free rundown of everything you need to know about AI as a business owner.

Topics covered in this episode include…

- Explanation of AI: Understanding artificial intelligence as a part of computer science that mimics human cognitive intelligence.

- AI in Everyday Technologies: Discussion on how AI informs the development of technologies like Siri, Alexa, Facebook, Instagram, TikTok, and Google.

- Generative AI Platforms: Overview of complex AI platforms like OpenAI’s ChatGPT and Google’s Bard and the use of "artificial neural networks".

- Role of Various Disciplines: Exploration of the roles of "deep learning", "machine learning", and "Natural Language Processing" in AI development.

- Importance of Training Data: Emphasis on the need for a significant amount of training data for AI's predictive analysis.

- AI and Predictability: Reflection on AI's inability to develop consciousness and its reliance on predictive analytics.

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OpenAI is worth around $29 billion at the start of this year. Microsoft invested $11 billion into it. It’s now worth $80-90 billion.

Meta is worth $791 billion. 

Amazon is worth $1.38 trillion. 

Google is worth $1.58 trillion.

Microsoft is worth $2.57 trillion.

Apple is worth $3.00 trillion.

All of these companies have one thing in common: They used our data to build their businesses.

Topics covered in this episode include… 

- Influence and control of tech giants: Discussing their agendas, their impact on our lives and minds.

- Importance of digital literacy: Highlighting the need for critical thinking in the digital age.

- Data Privacy: Discussing misuse of data, privacy policies and the need for regulation.

- OpenAI controversy: Addressing concerns about data mining from the internet.

- Tech billionaires' relationship with data: Analysing their disregard for solving genuine human problems.

- Importance of data protection: Discussing the power of data, the need for protection and its impact on personal autonomy.

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Topics covered in this episode include… 

- Importance of vast data availability in internet for AI development, ending its "winter" phase

- Impact of internet revolution on data sharing, providing access to large data sets for AI research

- Internet's role in boosting collaborative work and technology development, accelerating idea exchange and research 

- Utilisation of collective processing power of multiple computers via the internet for complex model training, especially with cloud computing

- Legal and privacy concerns arising from exploitation of personal data by tech giants, underscoring the permanence of internet data.

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AI is the reasoning or logic behind things - it’s a way of automating tasks that would normally require cognitive intelligence. 

AI innovation and development started in the 1950s, and progressed steadily until it stalled because of a lack of data. You can’t create vast neural networks and large language models without training data.

This is where the internet and Big Data have accelerated the technological developments of the past 5 years - because the learning capacity of AI models exploded.

Topics covered in this episode include… 

- Definition and perception of AI 

- Historical context and origins of AI 

- AI's impact on various sectors (e.g., internet, finance, logistics)

- Evolution of automation in industries and homes

- The role of AI in automation and cognitive tasks

- The influence of Big Data and the internet on AI development

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When we use AI in a way that frees us from repetitive, monotonous tasks so we can spend more time pursuing creative things or subjective things that take more time, we end up with more space, energy, and profit to be able to work on the things we love with incredibly skilled humans - without the hamster wheel hustle.

AI gives us the opportunity to do the things that are creative, unpredictable, human, messy, relational, and fun by cutting down the amount of time it takes to do the stuff that is outside our joy zone.  

Because logic doesn’t change the world.

Topics covered in this episode include… 

- Fear and uncertainty of AI replacing human jobs

- Potential misuse of AI for personal gain

- AI's redefinition of labour as cognitive processing

- Limitations of AI's ability to mimic human emotions and impulses

- Benefits of AI in freeing up time for creativity and joy 

- The potential for AI to revolutionise how we work and live.

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AI is not a fad. It’s not a passing trend. It’s not (just) the latest hot topic.

We can't just ignore it and expect it to go away. It has already been intrinsic to the growth of all the major players in the online space for the past 10+ years - and has even controlled 25% of the world’s money for the last 35 years.

So in this mini-series, I’m gonna give you a rundown of the key things you need to know about AI - and whether it will replace humans. (It won’t, but I’ll get to that.)

Topics discussed include…

- AI's role in search engine algorithms

- Existential questions raised by AI

- AI's impact on societal values

- Importance of empathy, compassion in business

- Preserving human value in productivity-focused industries

- Launch and impact of ChatGPT

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