Bittensor’s Rise, Meta’s Llama Goes Cloud, & AI Now Writes Your Code | E2119

Key Concepts

• Bit Tensor: A crypto project aiming to incentivize a decentralized network for AI computation.
• Tao (TOW): The coin used within the Bit Tensor network, inspired by Bitcoin's limited supply.
• Subnets: Individual projects within the Bit Tensor ecosystem, each with its own specific focus and potentially its own sub-token.
• Incentivization Network: A system where participants are rewarded with crypto (Tao) for contributing resources (e.g., GPU compute) to the network.
• Decentralized Compute: Utilizing a distributed network of computers to perform tasks, offering an alternative to centralized cloud providers like AWS.
• AI Training & Inference: The processes of training AI models (requiring significant compute) and then using those models to make predictions or decisions (inference).
• Eeky Guy (Ikigai): A Japanese philosophy for finding purpose, adapted here to help startups identify their ideal customer and value proposition.
• Return to Office (RTO): The trend of companies requiring employees to return to working from a physical office location.

Bit Tensor: Bitcoin Meets AI

• Project Overview: Bit Tensor is a crypto project inspired by Bitcoin, aiming to create a decentralized network for incentivizing AI computation. The project's coin is called Tao (TOW), with a limited supply of 21 million coins, mirroring Bitcoin's scarcity.
• Purpose: The primary goal is to build an incentivization network for AI, utilizing distributed computing power. Instead of solving arbitrary math problems like Bitcoin mining, Bit Tensor aims to put GPU resources to work on useful AI tasks.
• How it Works:
  • Individuals contribute GPU resources to the network.
  • These resources are used to run AI jobs for users.
  • Contributors are rewarded with Tao coins for their participation.
• Subnets: The Bit Tensor network is divided into subnets, each focusing on a specific area (e.g., AI compute, data annotation). Each subnet can have its own coin.
• Subnet Examples:
  • Shoots: A decentralized compute network for AI, offering serverless deployment options. Claims to be significantly cheaper (85% less) than AWS.
  • Targon: Another subnet providing decentralized compute for AI, with Fiat Rails.
  • Ready AI: A subnet focused on decentralized data annotation for AI training, similar to Scale AI.
• Governance: Anyone can start a subnet by staking Tao. The amount of Tao staked determines the subnet's emissions (rewards).
• Subnet Economics: Subnets have their own market caps, and the size of the market cap determines how much of the overall Tao emissions they receive. This creates a market and competition between subnets.
• Notable Individuals: The founders are a team of engineers located around the world. They are doxed (not anonymous). Barry Silbert is heavily invested in Bit Tensor.
• Potential: Mark Jeffrey believes Bit Tensor could become as significant as Bitcoin and Ethereum.

Decentralized Compute and AI

• Shoots and Targon: These subnets offer a decentralized alternative to cloud providers like AWS for running AI workloads.
• Cost Savings: Shoots claims to offer compute at 85% less than AWS. This is achieved through the subsidy provided by Tao emissions.
• Model Availability: Shoots claims to have new AI models available faster than traditional cloud providers.
• Meta's Strategy: Meta is partnering with Grock and Cerebras to offer hosted AI models, potentially competing with AWS in a specific slice of the cloud computing market.
• AI Cost Trend: Mark Jeffrey believes the overall trend is that the cost of AI compute will approach zero due to factors like decentralized networks and open-source models.

AI-Generated Code

• Adoption Rate: AI is rapidly becoming a significant contributor to code development.
• Statistics:
  • Over 30% of code committed at Google comes from AI sources (Sundar Pichai).
  • 20-30% of code at Microsoft is written by AI (Satya Nadella).
  • Cursor writes approximately one billion lines of accepted code per day.
• Impact: AI-generated code is expected to significantly increase developer productivity, potentially reducing the number of developers needed for projects.

Venture Capital Outreach

• AI-Generated Outreach: The increasing use of AI for cold outreach to VCs is pushing investors back towards warm introductions and referrals.
• Effective Outreach Strategies:
  • Curated List: Create a targeted list of VCs who are likely to invest in your company.
  • Warm Intros: Prioritize getting warm introductions to VCs on your list.
  • Thoughtful Emails: Craft personalized emails that demonstrate you understand the VC's investment focus.
  • Conciseness: Keep emails short and to the point.
  • Value Proposition: Clearly state the value you offer to the VC.
  • Clear Ask: Make a specific request.
  • Demonstrate Value: Show a chart with growth metrics.
  • Offer Flexibility: Be willing to meet anytime, anywhere.
• Alexis Ohanian's Advice: Focus on empathy, understanding the recipient, and demonstrating value upfront.

Layer Next: Strategic Business Intelligence

• Product: Layer Next is a strategic business intelligence platform that uses AI to help CFOs generate strategies for business growth and efficiency.
• Challenge: Onboarding new customers is difficult because their data is often not AI-ready.
• Example Use Case: Helping a company decide whether to hire more salespeople by analyzing sales data, cash flow, and potential revenue impact.
• Ideal Customer Profile: Companies with sales teams, Salesforce data, and a legacy accounting system.
• Eeky Guy Framework: Applying the Eeky Guy philosophy to identify the ideal customer, their needs, and how Layer Next can provide value.
• Bear Hug Strategy: Embedding the Layer Next team within a lighthouse customer's office to gain a deeper understanding of their needs and data.

Return to Office (RTO)

• Reasons for RTO:
  • Increased speed and efficiency.
  • Higher energy levels and intensity.
  • Improved culture.
  • Competitive advantage.
  • Reduced abuse of work-from-home policies.
  • Enhanced creativity.
• Benefits for Young Employees:
  • Mentorship opportunities.
  • Professional development.
  • Socialization.
  • Access to the "locust of power" (senior leadership).
• Remote Work Considerations: Remote work may be suitable for high performers with defined roles and tight skill sets.

Conclusion

The discussion covers a range of topics, from the potential of decentralized AI compute networks like Bit Tensor to the evolving landscape of venture capital outreach and the ongoing debate about return-to-office policies. Key takeaways include the importance of identifying a clear value proposition, understanding the needs of your target audience, and adapting to the changing dynamics of the business world.