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Event: Agents in Production
Prosus and MLOps.Community are hosting the Agents in Production Event on November, 13th. The event will feature top speakers like Thomas Wolf - Co-Founder of HuggingFace, Prashanth Chandrasekar - CEO of Stack Overflow and Nathan Benaich from Air Street Capital, along with experts from OpenAI, Stanford, Replit, and more! The event focuses on bringing AI agents into real-world production, covering a range of topics from autonomous payment agents to customer service and analytics solutions. Join the global ML/AI community to explore practical applications and proven strategies for deploying and scaling AI agents across sectors like e-commerce, food delivery, SaaS, and more.
Click here to particiapte in our study! YouGot.Us is conducting a research project about AI Agents and invites all Agents in Production participants to join the survey. We will provide a report to all survey participats when completed.
Insights: LLMs in Production
For entrepreneurs and business owners eager to bring Large Language Models (LLMs) into their organizations, the process often raises essential questions: Where can LLMs add the most value? What technical resources are required, and how can data privacy be maintained? The Insights and LLM in Production report offers answers to these questions and more, guiding both seasoned practitioners and newcomers. It provides a roadmap for identifying high-impact applications—whether automating customer support, enhancing data insights, or optimizing content generation—and understanding infrastructure needs, such as cloud-based versus in-house solutions. With detailed guidance on data governance, compliance, and team composition, this resource helps business leaders make informed decisions about adopting LLMs effectively and ethically. For those looking to stay ahead in a competitive landscape, the report offers the strategic insights needed to leverage LLMs confidently and responsibly.
The findings from the “AI in Production” event, held in February 2024, reveal a stark disparity in organizational LLM maturity across industries and company sizes. AI startups and organizations within the AI and ML sector are leading in LLM expertise, with a significant proportion of respondents identifying as Experts or Advanced in their adoption and application of these technologies. In contrast, traditional industries such as Data Analytics, Healthcare, and large enterprises, including Fortune 1000 companies, report lower levels of maturity. Our study highlights that while smaller, AI-focused companies are making strides in leveraging LLMs, many larger and more established businesses are still in the early stages of adoption. This trend underscores the critical need for greater investment in AI capabilities and upskilling within traditional industries to remain competitive in an increasingly AI-driven market.
About MLOps Community
The MLOps Community addresses the rapidly expanding necessity for sharing real-world Machine Learning Operations (MLOps) best practices among engineers actively working in the field. Although MLOps and DevOps share considerable common ground, the distinctions between them are just as significant. Recognizing the need for a dedicated platform to tackle the distinct challenges encountered daily in constructing production AI/ML pipelines, the MLOps Community was born. United by a shared commitment to innovation and excellence, MLOps Community offers a space where professionals can collaborate, share insights, and learn from each other. Discover more and become part of the growing network at MLOps Community.
About YouGot.Us Insights
At YouGot.us Insights, we stand at the intersection of advanced Data Science and market research. Our ethos is centered around harnessing the immense power of data to unlock transformative business insights, bridging the gap between information and action. YouGot.us Research is committed to open research and sharing our results, embracing a philosophy that knowledge should be accessible to all. Our dedication to transparency and collaboration is fundamental to our mission, as we believe that shared insights can foster innovation and drive progress across industries. Machine Learning Hangout is the online community associated with YouGot.us.
Insights: Uneven Access to ML Resources Across Industries and Company Sizes
Access to high-cost machine learning (ML) resources like GPUs and cloud platforms (e.g., AWS, Databricks) varies widely across industries, company sizes, and team sizes. This recent study, based on data from the ‘Data Engineering for AI’ event, highlights significant disparities in resource availability.
This study underscores the importance of developing strategies to democratize access to ML resources, enabling broader innovation across all sectors and company sizes.
Access to high-cost machine learning (ML) resources like GPUs and cloud platforms (e.g., AWS, Databricks) varies widely across industries, company sizes, and team sizes. This recent study, based on data from the ‘Data Engineering for AI’ event, highlights significant disparities in resource availability.
Key Findings
Industry Differences: Tech-heavy sectors such as Computers/Technology and Energy/Mining report better access to ML resources, with a majority rating their access as “Good” or “Excellent.” In contrast, industries like Retail/Sales and Insurance/Risk Assessment struggle, with few participants reporting strong resource availability. This gap may hinder these industries’ ability to keep up with tech-driven innovation.
Impact of Company and Team Size: Larger companies (10,000+ employees) and teams report higher access to ML resources, while smaller organizations face significant challenges. Limited budgets and competing priorities likely drive this disparity, putting smaller companies at a disadvantage in leveraging data-driven insights.
Implications: These access gaps highlight the need for more equitable resource availability across industries. Without affordable and scalable access to ML infrastructure, smaller and less tech-focused sectors risk falling behind in an increasingly data-reliant landscape.
Watch YouGot.Us Co-Founder Martin Stein on the Posit Data Science Hangout Podcast
Martin Stein is a seasoned data scientist, entrepreneur, and Chief Analytics Officer. With over 20 years of experience in AI, machine learning, and data science, he brings a wealth of expertise, developing cutting-edge MarTech solutions that empower marketing leaders to make data-driven decisions to maximize their investments. Stein is also the co-founder of Bend.ai, an AI/machine learning company acquired by Conversion Logix. His career includes significant roles at Apple, IDG/IDC, G5, RStudio, and startups like FileThis, Defined.ai, and Union.ai. Throughout his career, he has demonstrated a proven ability to build and scale products to over $200 million in revenue.
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