Episodes
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The last barrier to enterprise adoption of AI was memory. Baking into every prompt what the algorithm needed to know, was enough to send business leaders scurrying for the Luddite hills. But now Google (with Gemini and DeepMind's Mustafa Suleyman) and Microsoft are promising AI with memory. This will change so much about how we use AI - and make things so much more effective, and efficient. Let's get stuck in!
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Understanding human behaviour is critical to business success.
Behavioural science informs every growth stage and product decision - yet so few businesses pay any attention to human behaviour and psychology.
This new development makes a hugely insightful and practical corpus of psychological and behavioural data useful for everyone.
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Missing episodes?
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Tired of research and development (R&D) bottlenecks? Today's episode of AI Today explores how AI can supercharge product development by rapidly uncovering game-changing insights from mountains of data and even suggesting testable solutions, accelerating the journey from idea to market.
Discover how AI tools are democratising access to powerful insights, potentially levelling the playing field for smaller companies and fuelling a surge in innovation across all sectors.
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I've tested 20 AI coding editors. My tech skills are basic, at best. None turned my ideas into apps.
That's when I found Databutton.
And now I'm an app developer.
Listen in to find out how Databutton has given the world's 8 billion inventors a chance to bring their ideas to life...
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Here at AI Today, we know how to listen.
We spent hours analysing Lenny Rachitsky - host of Lenny's Podcast - interviewing pro prompt engineer Mike Taylor to bring you this deep dive into all the techniques, tools, and tactics to rock your business.
Enjoy this special edition of a very special show...
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Botto's 15,000 curators are celebrating a big win this week after six of their carefully-chosen, pixel-pushed masterpieces, sold for more than $350,000 at a Sotheby's auction in New York. It's a story that belongs in a museum. Just when we thought it was safe to come out after NFTs' baffling popularity flare-up of the very early 20s, we're here again. At least Beeple created his own art...
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Imagine if you had massive balls - crystal ones - to accurately forecast future business needs.
That's one of the thousands of ways autonomous agents - popularised in organisations of all sizes through Microsoft Copilot Studio - can build better businesses.
These agents can send reports to your senior leadership team identifying inefficiencies or opportunities across the organisation. Then the HR squad can decide whether to upskill colleagues or hire in new ones. All before shit hits the fan!
Autonomous agents will change everything, Taste the future on today's episode of AI Today!
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Retrieval augmented generation is how we used to chunk content in huge corpuses of data. Now there's a new sheriff in town - contextual retrieval preprocessing, or contextual RAG. No more relying on keywords; now we're talking hidden relationships between data, which means you can better respond to context inside queries.
This isn't just about finding information faster, it's about understanding the meaning behind it. Imagine your knowledge base becoming a mind-reader, anticipating needs and delivering precisely what's required, instantly.
We're talking about boosting agent productivity, empowering them to become knowledge ninjas, and transforming customer interactions into personalized experiences. Get ready to unlock growth by maximizing efficiency and creating a customer service dream team!
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Let's take a look at how the latest version of Copilot can change the game for your business.
Imagine a manufacturing company developing a new electric vehicle (EV) charging station. This complex process involves multiple steps and teams, using various applications and datasets.
Market research: Copilot can analyse large datasets and generate visualisations to quickly identify key insights by analysing market trends using Excel with Python to forecast demand, pricing, and competitor analysis.
Design and engineering: Copilot can summarise key design discussions from Teams meetings and highlight potential issues, saving engineers time, and facilitating quicker decision-making, by tracking changes and feedback, and summarising discussions, while engineers collaborate on designs using OneDrive and SharePoint.
Sourcing: Copilot compares supplier bids and contracts using OneDrive, ensuring compliance with internal policies. AI surfaces discrepancies and highlights areas needing attention, streamlining negotiation and contract finalisation.
Prototyping and testing: Share test results and feedback across teams using SharePoint and Teams. Copilot can automatically generate reports summarising test data from various sources and identify key performance indicators, helping engineers iterate designs efficiently.
Marketing and sales: Create compelling marketing materials and sales presentations using PowerPoint and Copilot. Copilot can generate presentation drafts based on product specifications, market research, and competitor analysis, ensuring marketing messages are impactful and consistent.
Another major development is Copilot Agents - completing seemingly disconnected tasks forming a single activity.
In the EV charging station development process, a critical step involves collecting and analysing customer feedback during the pilot testing phase.
Traditionally, this process is manual and time-consuming:
Technicians gather feedback from pilot customers through surveys, emails, or phone calls.
This data is collated and manually entered into spreadsheets or databases.
Data analysts then process this information to identify trends, issues, and areas for improvement.
These insights are then shared with engineering, design, and marketing teams.
Copilot Agents can radically transform this process by automating these tasks and unlocking unimaginable possibilities:
Automated feedback collection: A Copilot Agent could be deployed to automatically gather feedback from pilot customers through various channels like in-app surveys, SMS messages, or even voice assistants. This agent could be trained to understand natural language and extract key insights from customer responses.
Real-time data analysis: As the agent collects feedback, it can use Excel with Python to perform real-time data analysis, identifying recurring issues, sentiment trends, and feature requests. This eliminates the need for manual data entry and processing, providing instant insights.
Proactive issue resolution: The agent could be programmed to automatically generate support tickets for reported issues, routing them to the appropriate teams for resolution. It could even suggest solutions based on previous support interactions or knowledge articles, significantly speeding up the resolution process.
Personalised communication: The agent can also be used to communicate with customers proactively, acknowledging their feedback, providing updates on issue resolution, and even offering personalised tips or recommendations based on their usage patterns.
By automating tasks, connecting data, and surfacing insights, Copilot reduces time to market and enhances the final product.
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If there's anyone left in the world yet to be convinced AI is changing it, have a chat with Meng To (@mengto on X). He just wrapped up Dreamcut.ai - what he calls his perfect video editor - after spending three months writing 50,000 lines of code with Anthropic's Claude AI.
The application is incredible. As is Meng's generosity - he's giving away the codebase.
Enjoy this deep dive into the amazing story of Dreamcut.ai.
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Forget everything you thought you knew about AI assistants. We're not talking simple chatbots that can barely string a sentence together. Claude 3.5 Sonnet, the latest iteration of Anthropic's groundbreaking language model, can actually use computers like a human. It can see the screen, move the mouse, click, type, and even navigate complex software. Think about that for a second. An AI that can control your computer. That can access the vast world of information online, manipulate data, and even write and execute code. It's a power we've only dreamed of, and it's here now.
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Engineering teams are frazzled. And we've all been down the Cursor, Aider, Cline, Bolt, and Replit rabbit roles questing for AI coding nirvana. But there are more potholes in the process than a worn-out highway. Enter Solver - self-proclaimed level 4 FSD for coding. Let's take this one for a spin...
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Now anyone can know what everyone is doing in real time!
xAI's API gives you access to the 560Gb of data generated every day by the millions of users on X, formerly Twitter.
There are some fantastic opportunities to integrate this unique and ever-changing dataset into your applications.
And you've never before had access at scale to the thoughts and behaviours of your current and future customers.
Let's dive in!
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Business is a spider's web of complex processes. And up until now, it's been super hard to get AI working on multi-task processes, without some PhD-level hacking which, unless you're using open source, locally-hosted LLMs, could come unstuck at any time.
Agora solves this. It suggests a rational approach to agentic AI by connecting the bots through a single communication protocol.
In turn, business tasks previously doable only by humans suddenly become perfectly feasible for our silicon siblings.
Super excited about this one. Please enjoy!
Podcast based on this research paper:
A SCALABLE COMMUNICATION PROTOCOL FOR NETWORKS OF LARGE LANGUAGE MODELS
Available at: https://arxiv.org/pdf/2410.11905
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Efficiency. Productivity. Growth. That's why we're here. And on today's show, we're hitting all three with the force of a bullet train. 3 AI experts share how they create the best results, in three totally different ways. This is a listen that you can't afford to miss. Enjoy the show!
How product manager Tal Raviv saves a ton of time and generates incredible insights: https://creatoreconomy.so/p/how-experienced-pms-use-chatgpt-tal-raviv
Christopher Penn's advanced AI prompting: https://open.substack.com/pub/almosttimely/p/almost-timely-news-advanced-prompt
No more bad outputs with structured generation, with Remi Louf: https://www.youtube.com/watch?v=aNmfvN6S_n4
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AI's made its name in the digital space. But thanks to Archetype AI, it's broken away from its silicon prison to learn about our physical world. Archetype's Newton, a Large Behaviour Model, is currently crunching datafrom sensors like cameras and radars to create a unified representation of the physical environment. This allows for real-time insights and predictions, enabling applications such as smarter homes, safer vehicles, and improved industrial processes. Archetype is currently working to make Newton accessible to everyone, allowing individuals and businesses to utilise its capabilities through an API and various applications.
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Imagine a world where a doctor, armed with an AI-powered assistant, can diagnose diseases like pancreatic cancer earlier, potentially saving thousands of lives annually.
This isn't science fiction; it's the reality Microsoft is building through its AI for Health program.
This program, like a master conductor, is orchestrating an AI symphony with tools like cutting-edge imaging analytics, allowing AI to identify tumours often missed by the human eye.
It's not just about improving diagnoses, it's about improving access to healthcare too. Imagine a virtual health village, accessible 24/7, where AI-powered chatbots like 'Quitbot' can help people quit smoking or guide them through symptom triaging.
This vision is becoming a reality with Azure Health Bot, which can be easily customised to support a wide range of healthcare scenarios.
The power of these breakthroughs lies in the integration of diverse data types - medical imaging, genomic data, clinical records - all analysed by AI models in Azure AI Studio.
It's like having a super-powered detective, capable of analysing millions of clues at once, uncovering hidden patterns and insights that could revolutionise healthcare. This could lead to more personalised treatment plans, faster drug discovery, and a deeper understanding of complex health issues.
Microsoft is building a future where healthcare is more accessible, efficient, and effective - a future where AI empowers both patients and medical professionals to achieve better health outcomes.
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Imagine your marketing team brainstorming hundreds of genuinely inspired ideas in seconds.
That's the potential of Thought Preference Optimisation (TPO), a new AI technology from Meta.
TPO is like giving your AI a brain. Unlike standard AI, which rushes to spit out the first answer, TPO takes time to 'think' things through. It generates internal thoughts, invisible to you, and uses them to refine its responses before presenting the best one.
This is a big development for marketing. In trials, TPO outperformed standard AI on key marketing and creative writing benchmarks.
Think of it as your AI team going through rounds of internal brainstorming and presenting you with only the most polished, effective ideas.
Here's a quick example:
Prompt: Write a tagline for a new brand of sustainable sneakers made from recycled ocean plastic.
Standard LLM Output:
Walk with the ocean.
TPO Output:
1. Internal Thoughts:
The tagline should be concise and impactful.
It should highlight the sustainability aspect.
It should appeal to the target audience who care about the environment and style.
Possible themes: ocean conservation, recycled materials, stylish and eco-conscious.
2. Tagline: Style that tides the world.
The standard LLM output is quick and direct, but lacks depth and creativity. It fails to convey the unique selling proposition.
The TPO output demonstrates a more deliberate and thoughtful process. The internal thoughts reveal how the AI considers different factors and explores potential themes before arriving at a tagline that is more creative, memorable, and relevant to the brand's mission.
When can you get your hands on this? While still under development, TPO builds on the latest AI research from Meta and OpenAI.
Find out more on the latest episode of AI Today...
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Former Deloitte consultant Varun Kulkarni spent 8 months honing his application strategy to score a huge payday as a senior AI product manager gig with Cisco. On today's show we explore how he did it - so you can, too...
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AI is a paradigm shift for thinking and understanding. Our old frameworks and models are being challenged into obscurity by a new way of looking at the world. And even the things we used to think of as a human-centred endeavour - inventing previously inconceivable things to change lives - can now be generated by our digital colleagues. Today's show is designed to be challenging; stick around to have your mind blown...
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