Navigating AI: Strawberries, Autonomous AI and more

September 16, 2024

Welcome to this week’s AI Trailblazers Newsletter and thank you for making us your go-to source for relevant AI business news.

Open AI continues to push the envelope with the unveiling of o1 or Strawberry model to battle complex tasks more proficiently than previous models. It’s a landmark achievement and marks the next step in the quest to mimic human reasoning. Also in this week’s edition, the argument for CMOs to lower their AI expectations. Discover more below.

Mark your calendars: the AI Trailblazers Growth Summit is happening on October 30th in New York. Purchase your tickets now at the early bird rate, and stay tuned for agenda details. In the meantime, check out highlights from our last summit, and email us if you're interested in partnering.

OpenAI Unveils Its ‘Strawberry’ Model

OpenAI has unveiled o1, its first model in a new "reasoning" series designed to tackle complex tasks like coding and math with improved accuracy. The Verge reports that unlike previous models, o1 uses a new training approach focused on solving problems step-by-step, resembling human reasoning. Despite its advanced capabilities, the model is more expensive and slower than its predecessors, marking it as an early preview in OpenAI's broader goal of achieving human-like intelligence.

  • OpenAI has introduced the o1 model, the first in its "reasoning" series, designed to handle more complex problems, such as coding and math. It also launched o1-mini, a smaller and cheaper version. However, o1 is slower and more expensive to use compared to GPT-4o.

  • The o1 model is trained with a new optimization algorithm and reinforcement learning, which teaches the model to solve problems on its own. This training allows o1 to process queries step-by-step, mimicking human-like thought processes. Despite this, hallucinations still occur, though at a reduced rate.

  • In various tests, o1 outperformed GPT-4o significantly, including solving 83% of problems in the International Mathematics Olympiad and reaching the 89th percentile in programming contests. However, it is weaker in factual knowledge and lacks web browsing and file processing abilities.

  • OpenAI aims to use o1's reasoning capabilities to push toward autonomous systems that can make decisions and take actions. While o1 represents progress toward human-like intelligence, it remains expensive and slower than ideal for developers, emphasizing its "preview" status.

AI Trailblazer Takeaways: It's one small step for AI, one giant leap for humankind! While OpenAI's o1 (Strawberry) marks a significant advancement in AI's reasoning abilities, identifying the right use cases within your function or organization remains the next challenge—one that even Strawberry may not fully address yet.

Powerful and Autonomous

Agentic AI is an emerging technology that promises to revolutionize industries by enabling autonomous systems capable of making decisions, solving complex problems, and adapting to changing circumstances. Forbes reports that unlike traditional AI, agentic AI operates with enhanced autonomy, offering groundbreaking potential across sectors like healthcare, finance, and business operations. While the benefits are significant, challenges such as ethical concerns and job displacement highlight the need for thoughtful integration of this advanced technology.

  • Agentic AI offers enhanced autonomy and problem-solving abilities. Unlike traditional AI, agentic AI can act independently to achieve specific goals, making decisions, planning actions, and learning from experiences. Its chaining capability allows it to break down complex tasks into smaller steps, such as creating an entire website autonomously. This level of intelligence transforms AI into a more proactive and adaptable digital assistant.

  • Agentic AI is poised to revolutionize several industries. In business operations, it can manage supply chains, optimize logistics, and reduce costs through real-time decision-making. Healthcare may benefit from agentic AI as a round-the-clock health assistant, monitoring patients and adjusting treatments dynamically. Additionally, industries like software development, cybersecurity, and HR could see massive efficiency improvements with these autonomous systems.

  • Agentic AI's adaptability and personalization stand out. Its ability to adjust strategies based on changing data makes it highly effective in dynamic environments, such as financial markets and scientific research. AI agents can provide tailored experiences, from personalized therapy support in healthcare to investment management in finance. This level of customization and scalability makes agentic AI versatile across numerous applications.

  • Challenges and ethical concerns accompany agentic AI’s growth. There are important questions surrounding data privacy, decision-making transparency, and accountability, especially as these systems take on more autonomy. The "black box" problem makes it hard to understand AI decisions, which raises issues of trust in high-stakes situations. Additionally, the potential for job displacement requires careful consideration of how agentic AI will impact the workforce.

AI Trailblazer Takeaways: If properly administered, agentic AI could revolutionize many industries and make things easier for all of us…..and empower us to become super-employees.

The AI Gamble for CMO’s

According to Ad Age, Chief Marketing Officers (CMOs) are facing a critical challenge as their expectations for quick returns on AI investments clash with the reality of the technology's gradual development. According to Gartner research, many AI-driven projects may be abandoned by 2025 due to these unrealistic expectations. To succeed, CMOs need to shift their focus from immediate financial gains to long-term change management and data readiness, all while navigating the complexities of AI implementation and organizational resistance.

  • CMOs' Unrealistic AI Expectations: Many Chief Marketing Officers (CMOs) expect immediate financial returns from AI investments, but Gartner research shows that generative AI requires time and continued effort to deliver results. At least 30% of AI-driven projects could be abandoned by 2025 due to these unrealistic expectations. Short-term success will depend on embracing indirect outcomes like change management rather than immediate profit.

  • Challenges with Generative AI: The costs of implementing generative AI are substantial, with solutions like virtual assistants requiring millions in upfront costs and ongoing maintenance. CMOs must recognize that AI is not a one-time investment, but a continuously evolving technology needing constant updates. Custom AI models, while effective, also come with hefty price tags and time investments, complicating expectations for quick results.

  • Misunderstandings about AI Functionality: CMOs often misunderstand how AI operates, expecting identical outputs from the same input, which is rarely the case. Smoothing AI-generated outputs requires significant resources, including time and infrastructure. The challenge lies in aligning AI's capabilities with marketing needs while accepting its inherent variations and limitations.

  • Focusing on Change Management: Instead of immediate ROI, CMOs should prioritize areas like data hygiene, technology adoption, and building trust both internally and externally. With only 4% of CMOs reporting AI-ready data, preparing organizational culture and governance for AI is critical. Addressing employee resistance and customer skepticism, along with clear AI goals, can help navigate the challenges and set the stage for long-term success.

AI Trailblazer Takeaways: AI could help marketers in many ways but where do you start. Perhaps the best place is with simple tasks and tools already in use with many 3rd party vendors such as email content, personalization and deployment. Get a quick win in and then go back for more.

Quote of the Week

“AI is a tool. The choice about how it gets deployed is ours.“

- Oren Etzioni

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