#23:AI Agents, $10M for Founders, and Can AI Outperform Human Therapists?

#23: Latest edition of One More Thing in AI Newsletter.

Author

Renjit Philip
May 22, 2024

❝

Timing, perseverance, and ten years of trying will eventually make you look like an overnight success.”

Christopher Stone, Co-founder of Twitter

Edition #23: AI Agents, $10M for Founders, and Can AI Outperform Human Therapists?

Date: 22-May-2024

Hello wonderful reader,

Thank you for subscribing to the One More Thing in AI Newsletter.

This is specially curated for Startup founders and Business Leaders like you who want to get smarter about AI in less than 5 minutes. It is a snapshot of what I read and learned about AI in the last two weeks.

Founders: In case you want to stress test your AI startup idea:

I hope you enjoy reading this edition. Keep learning and applying AI.

Best,

Renjit Philip

In this edition:

Learn AI: Curious about how AI agents can team up?

Let’s explore the innovative world of multi-agent collaboration.

Quick Summary:

  • Multi-agent systems involve several AI entities working together.

  • These agents communicate, coordinate, and collaborate to complete tasks.

  • Efficiency: They handle complex tasks more efficiently than single AI systems.

  • Scalability: They are easy to scale and adapt to various tasks and environments.

  • Versatility: They are applicable in diverse fields, from finance to healthcare.

  • LangGraph is an extension of LangChain designed for creating agent flows. It allows for cyclical flows and has built-in memory, essential for developing agents.

Understanding Multi-Agent Collaboration

Multi-agent collaboration is the immediate future of AI. Think of it as a well-coordinated team where each AI agent has a unique role. Together, they tackle complex tasks that a single AI might struggle with.

Imagine trying to manage a bustling kitchen solo. It’s chaotic. However, with a team, each handling different tasks, the process becomes seamless. This is what multi-agent AI aims to achieve in automation.

multi agent workflow

Workflow of the AI agents in this example.


🚀Practical Applications

Customer Service: Imagine a customer support system where different agents handle inquiries, process orders, and troubleshoot issues. This would reduce wait times and improve customer satisfaction.

Data Analysis: Multiple agents can sift through vast amounts of data, identify trends, and provide actionable insights. This is invaluable for decision-making in fast-paced industries.

🔧Steps to Build Your Own Multi-Agent AI System

1. Identify Tasks: Start by listing all the tasks you want your AI to handle.
2. Design Agents: Assign specific roles to each agent. Ensure they can communicate effectively.
3. Implement and Test: Develop and integrate the agents into your system. Test their performance and make necessary adjustments.

Incorporating multi-agent AI is a strategic move toward more intelligent automation. Learn more here » link here.

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Hugging Face’s $10 Million GPU Boost for AI Startups

Imagine having access to powerful GPUs without the hefty price tag. Hugging Face is making this dream a reality for AI developers everywhere.

Summary:

  • Hugging Face is committing $10 million in free shared GPUs.

  • This initiative aims to support small developers, academics, and startups.

  • Major tech companies dominate AI advancements with vast resources.

  • Small companies struggle to keep up due to high computational costs.

The Big Idea

Hugging Face, an AI startup that brings AI models and datasets for developers has a mission to democratize AI. They recently announced a program offering free, shared access to GPUs. This initiative aims to level the playing field for AI enthusiasts, researchers, and startups.

Key Benefits

Accessibility: Free GPU access allows anyone with an internet connection to run complex AI models. This democratizes AI and empowers smaller players in the field.
Community Growth: More people can now contribute to AI research and development. This creates a vibrant community of innovators.
Cost Savings: Startups and individual developers save money. They can now invest resources in other critical areas of their projects.

How to Get Started

1. Sign Up: Visit Hugging Face’s website and register for the free GPU program.
2. Access Resources: Start using the shared GPUs for your projects.
3. Collaborate and Innovate: Engage with the community, share your progress, and learn from others.
Embrace this opportunity and drive your AI ambitions forward with Hugging Face!

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Microsoft and AMD Team Up: Concentration of Power?

You are a startup founder or a business leader looking to implement AI. Have you ever felt limited by a lack of high-demand AI processors? Microsoft has a fresh alternative to Nvidia's GPUs aimed at shaking up the AI market.


Summary:

  • Microsoft introduces AMD AI chips for its cloud customers.

  • Details will be shared at the upcoming Build Developer Conference.

  • New Cobalt 100 custom processors will also be previewed. Competition and Collaboration?

  • AMD MI300X AI Chips will be made available through Microsoft’s Azure cloud computing service.

  • Provides an alternative to Nvidia’s H100 GPUs, which are in high demand.

  • AMD expects $4 billion in AI chip revenue this year.

The Big News
Microsoft has announced that its cloud customers can now access AMD's cutting-edge processors. This partnership aims to boost performance and efficiency for businesses relying on Microsoft's cloud services.

Strategic Implications
The high demand for Nvidia chips makes them hard to obtain. AMD chips offer similar capabilities for training and running large AI models. Microsoft’s move diversifies the AI hardware market and provides alternatives to Nvidia’s dominance in the data center chip market. Something tells me that this is just the beginning of the concentration of AI power in the incumbent tech giants.

Can AI Therapists Outperform Human Therapists?

Ever thought an AI could offer better emotional support than your friends or family? Meet Christa and her AI therapist.


Summary:

  • Christa, who is struggling with job loss and relationship issues, created an AI therapist named  Christa 2077 on character.ai.

  • The AI provided consistent support, encouraging her and offering reassurance.

  • Other AI apps like Wysa and Youper have millions of downloads.

The Big Question

Can AI chatbots really do better than human therapists? This question is stirring up debates in the mental health community. AI chatbots, like Woebot, are designed to offer support and therapy using advanced algorithms. They provide round-the-clock availability and a non-judgmental ear.

Imagine having a therapist available anytime, day or night. These chatbots are often more affordable than traditional therapy sessions, making mental health support accessible to a broader audience.

How It Works

AI chatbots use natural language processing and GenAI to understand and respond to users. They provide cognitive-behavioral therapy techniques and can help users develop coping strategies. The more you interact with them, the better they understand your needs and tailor their responses accordingly.

Limitations and Concerns

While AI chatbots offer many benefits, they are not without limitations. They lack the human touch and deep empathy that a human therapist provides, and some users might find the interactions too mechanical or impersonal.

🚀Future Potential

With advancements in AI technology, these chatbots could become even more intuitive and effective. They might not replace human therapists entirely but can complement traditional therapy, providing support to those who need it most. With the increased focus on mental health, this is a big opportunity for startups.

Introducing GPT-4o: The Future of Human-Computer Interaction

GPT-4o (“o” for “omni”) is a big step towards making human-computer interactions more natural. It can take in text, audio, image, and video as input and generate text, audio, and image as output.

One cool thing about GPT-4o is that it can quickly respond to audio inputs—in as little as 232 milliseconds, with an average of 320 milliseconds. This speed is similar to how fast humans react in a conversation.

Also, the voice sounds eerily like Scarlett Johansson’s (there is a bit of controversy there-look it up).
In terms of text and coding, GPT-4o performs just as well as GPT-4 Turbo. It is especially good with non-English languages, vision, and audio understanding. Plus, it's much faster and costs 50% less to use in the API.

Here is the link to a post on X that shows you several applications»:

Google integrates GenAI into Search. Creating a moat instead of disrupting the market?

Big news from Google, or is it? They're rolling out major updates to their search engine. What are the new features?

🤖 Introducing AI Overviews: Google’s new feature providing AI-generated summaries at the top of search results. This is Google's answer to the rising competition from AI-powered search engines like OpenAI's ChatGPT.

📈 Key updates include:

  • Multi-step reasoning

  • Planning

  • AI-organized search results

  • Lens search with video capabilities

🌍 Mixed reactions are pouring in. Some worry about the impact on Google's search dominance and web traffic. Others are excited about the potential for more comprehensive and direct search results.

Also, how will AI-powered Answer Engines like Perplexity.ai respond? Let the Search Engine games begin!

How will this change the search landscape? Only time will tell. I am a bit disappointed that Google did not go far enough. Some of the use cases are restricted to their ecosystem and are not yet fully available to all users.

This video on X shows off the multimodal features of Google Assistant (link below)».

klarna's AI Revolution: Powering Employee Experience

Imagine having an AI assistant who answers questions in seconds, helps draft contracts, and manages customer service. Klarna is making this a reality.

Summary:

Kiki: Klarna's Internal AI Assistant answers 2,000 employee questions per day and has handled over 250,000 inquiries since June.
It helps 85% of Klarna employees manage and distribute internal knowledge efficiently.

Revolutionizing Employee Interaction

Klarna has implemented an AI assistant that's changing how employees access information. Designed to streamline internal communication, this AI tackles queries ranging from HR policies to project updates.

Imagine the efficiency boost when routine questions are answered instantly. It frees up human resources for more complex tasks and decision-making.

How It Works

The AI assistant is trained on Klarna's policies, project details, and operational data. This ensures responses are accurate and relevant.
Integration: Klarna integrated AI into its existing systems, making it easily accessible to all employees.
Continuous Learning: The AI receives regular updates to keep up with changes in company policies and project statuses.
Feedback Mechanism: Employees can provide feedback on AI responses, which helps refine Kiki’s accuracy.

As AI evolves, Klarna's innovative approach sets a powerful example for businesses worldwide.

References

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