The GenAI Collective Community Newsletter
Week of January 8th, 2024
Upcoming Events
Thu, Jan 11th: 🧠 GenAI Collective x DataStax 🥞 AGI Enablers Summit 🤖
Mon, Jan 15th: 🧠 SVGAI - GenAI Collective 🧠 Generative AI Paper Read
Fri, Jan 19th: 🧠 GenAI Collective 🧠 Bytes && Bites SF Mixer
Thu, Jan 25th: ⚙️ MLOps Community x GenAI Collective 🧠 Tech Talks 🎙️
Tue, Jan 30th: 🧠 GenAI Collective 🧠 Inaugural Marin Meetup! 🍻
As we kick off our first newsletter of the new year, we are thrilled to feature our technical lead Matt White who dives into his thoughts and predictions for Generative AI in 2024. Read the full Medium article here!
Top Predictions and Trends for Generative AI in 2024
2024 promises to be another exciting year of generative AI innovations and adoption, but won’t be without its challenges. 2023 was all about mainstream awareness and excitement about generative AI with users and organizations taking steps to understand the technology and experiment with it. However, in 2024 the most significant impact of generative AI will be in the enterprise, where a renewed approach to solving business problems using generative AI solutions and software will be facilitated by the maturation of platforms that has taken place over the past year. This will ultimately reduce the organizational frictions that limited generative AI adoption in 2023.
The industry will see a shift towards democratized access to highly performant generative models that will challenge proprietary solutions. Enterprises will take a more realistic approach towards use case identification and organizations developing generative models will step up efforts to address model safety as legislators begin to make moves towards regulating AI technologies. Undoubtedly 2024 will be a great year for generative AI advancement, that will see a warming up of organizations to generative AI adoption, a toning down of the fear mongering we saw in 2023 about AI threats to humanity, and we are sure to see some key innovations that will help advance the technology.
Business Integration and Economic Development
In 2024, generative AI will significantly influence the business sector, with organizations integrating generative features to streamline operations, improve products and services, and create new revenue opportunities not previously easily achievable. A notable trend will be the shift towards smaller, more specialized open-source models deployed in self-managed deployments, especially in highly regulated industries. Democratization of generative AI in 2024 will challenge traditional proprietary solutions. Organizations will continue to experiment with generative AI but with clearer goals about intended outcomes, but even so, due to a lack of skills, experience, direction or budget, there is an anticipated success-to-failure ratio of 3:7 for generative AI projects reaching production across all organizations.
Model Development and Performance Innovations
The landscape will see the rise of Medium and Small Language Models (MLMs and SLMs), focusing on performance optimization with reduced resource needs. Open-source model production will challenge proprietary solutions, but no single model will match GPT-4 across all benchmarks. The first model to rival GPT-4 will likely be a composite of multiple models, operating in an ‘ensemble of experts’ architecture (not to be confused with the ‘mixture of experts’ single model architecture). Fine-tuning will become more accessible, and organizations will figure out how to more effectively collect and prepare their data, fueling more usage of domain-specific models.
Mainstream and End User Expectations
The initial hype around generative AI will transition to normalized expectations as the technology integrates more into everyday applications. Generative AI will become embedded in user interfaces or behind them, enhancing overall user experience, and becoming more accessible to those without prompt engineering skills. This transition will redefine both business operations and personal technology interactions.
Venture Capital and Investment Trends
The investment landscape will focus more on sustainable and innovative AI solutions offering a distinct competitive edge. “Thin wrapper” generative AI applications will become commoditized, leading to pivots and liquidations for many early generative AI startups. Startups focusing on hosting open-source AI models will face increased competition from hyperscalers, necessitating innovation.
Security, Privacy, and Ethical Considerations
Organizations will focus on black-box solutions like GPT-4 while evaluating open-source options as their performance increases. Generative AI governance will become better defined with standard industry models proposed, addressing data and model lineage, privacy, security, and conformance to regulations. More organizations will hire Chief AI Officers to facilitate innovation and integration of generative AI into their business.
Technological Advancements and Research
There will be a notable increase in specialized domain-specific open-source models reaching production-grade status that will create a marketplace for high-performing specialized models, transitioning away from highly and over-parameterized models. Alternate model architectures that will challenge the de-facto transformer architecture will surface, and all areas of the generative AI ecosystem will evolve with more focus and investment in generative AI application and agent frameworks. Innovations in GPU and memory-efficient optimizations will be crucial for widespread adoption of generative models that will bring down the operational costs for organizations.
The Road Ahead
As we approach 2024, the landscape of generative AI is set for transformative changes across various sectors. The integration into mainstream applications will deepen, making advanced tools more accessible and ingrained in daily life. This transition will not only redefine business operations but also how we interact with technology personally. Staying informed and adaptable will be key to keeping up with the rapid innovation in generative AI.
We would love to hear what from the community on their Generative AI predictions for 2024. If you would like to share your thoughts on the evolving role of AI in our professional and personal lives, hit up Matt or Eric on the community Slack or reach out via email at eric@gaicollective.com for a feature in our next newsletter!
If you would like to learn more about the latest in generative AI research and innovations, we would love to have you join our partner organization Silicon Valley Generative AI’s meetup.
Value Board
Our friends over at Superpower—a disruptive company helping people build a powerful, new lifelong relationship with their health—are looking for a founding engineer passionate about longevity and AI to join the team.
About Matt White
Matt is the Head of AI and Data at Amdocs and leads the Linux Foundation’s Generative AI Commons. He also teaches data science at UC Berkeley and is a strong advocate of open source and open science in AI. Matt leads the community’s technical arm and hosts biweekly paper readings at Silicon Valley Generative AI. With Matt, there’s no such thing as “too technical” 🤓
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