CybAI news - - Page 2333

21 May

Megadeals Explode Early In The Year As US Startups Gobble Up More $100M+ Rounds

stp2y0 CommentsRAG models

Want to keep track of the largest startup funding deals in 2024 with our curated list of $100 million-plus venture deals to U.S.-based companies? Check out The Crunchbase Megadeals Board. Although venture funding seems to be stagnating, more and more startups seem to be having an easier time securing really big funding rounds — that seemed to dry up last year — from investors. Rounds of $100 million or more — or megadeals — have exploded this year, as U.S.-based startups have collected 115 such rounds through mid-May, per The Crunchbase Megadeals Board. That is a 58% spike compared to…

21 May

Data Machina #253

stp2y0 CommentsViral News

The Google AI Blast . This week OpenAI released a new closed model called GPT-4o (as in omni): Hello GPT-4o, a model that can reason across audio, vision, and text in real time. It seems the model performance in many benchmarks wasn’t as good as many AI pundits expected.And while many people in the AI community were befuddled and discussing the “flirtatiousness” aspects of GPT-4o, then Google came in and blasted a massive AI storm including SOTA models, new powerful open models, and pretty amazing tools. Here’s my summary on what Google released: Gemini 1.5 Pro model updates: Lots of…

21 May

Reflections On Qualtrics X4: AI-Powered Research Is Promising If We Stick To The Research Basics

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Qualtrics introduced its AI-powered Strategy & Research suite at its summit, X4, and launched its “Strategic UX” product — officially entering the experience research space. The new product supports various UX research methods like video feedback, unmoderated usability testing, card sorting, and tree testing, and it leverages AI to generate insights and recommended actions. Adding UX research to its experience management solutions, Qualtrics aims to support organizations’ research efforts at scale with a single platform. Qualtrics AI was the highlight of the event as it aims to help users get deeper insights through interactive dashboards, data analysis, and recommendations on…

21 May

The Shift from Models to Compound AI Systems

stp2y0 CommentsAIai routers, compound ai systems, dspy, frugalgpt

AI caught everyone’s attention in 2023 with Large Language Models (LLMs) that can be instructed to perform general tasks, such as translation or coding, just by prompting. This naturally led to an intense focus on models as the primary ingredient in AI application development, with everyone wondering what capabilities new LLMs will bring. As more developers begin to build using LLMs, however, we believe that this focus is rapidly changing: state-of-the-art AI results are increasingly obtained by compound systems with multiple components, not just monolithic models. For example, Google’s AlphaCode 2 set state-of-the-art results in programming through a carefully engineered…

21 May

‘People are going to try to steal your secrets’ Dixon warns

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Kissimmee, Fla. – As U.S. intelligence agencies increase their reliance on commercial geospatial products and services, cybersecurity becomes a growing concern. “We create so many innovative solutions here in this country,” Stacey Dixon, U.S. deputy director of national intelligence, said May 6 at the 2024 GEOINT Symposium here. “Yet we lose a lot of that innovation to adversaries because we aren’t properly protecting it. Invest in your cybersecurity. Understand that people are going to try to steal your secrets.” Potential adversaries will seek access to commercial products directly as well as through intermediaries. Figure out how to prevent that, “because…

21 May

Scaling ML Experiments With neptune.ai and Kubernetes

stp2y0 CommentsGenAI

Scaling machine learning (ML) experiments is a challenging process that requires efficient resource management, experiment tracking, and infrastructure scalability. neptune.ai offers a centralized platform to manage ML experiments, track real-time model performance, and store metadata. Kubernetes automates container orchestration, improves resource utilization, and enables horizontal and vertical scalability. Combining neptune.ai and Kubernetes provides a robust solution for scaling ML experiments, making it easier to manage and scale experiments across multiple environments and team members. Scaling machine-learning experiments efficiently is a challenge for ML teams. The complexity lies in managing configurations, launching experiment runs, tracking their outcomes, and optimizing resource allocation.…

21 May

Measuring personal growth

stp2y0 CommentsRAG models

My founder friends constantly think about growth. They think about how to measure their business growth and how to get to the next order of magnitude scale. If they’re making $1M ARR today, they think about how to get to $10M ARR. If they have 1,000 users today, they think about how to get to 10,000 users. This made me wonder if/how people are measuring personal growth. I don’t want to use metrics like net worth or the number of followers, because that’s not what I live for. After talking with a lot of friends, I found three interesting metrics:…

21 May

Unveiling the Criticality of Red Teaming for Generative AI Governance

stp2y0 CommentsViral News

As generative artificial intelligence (AI) systems become increasingly ubiquitous, their potential impact on society amplifies. These advanced language models possess remarkable capabilities, yet their inherent complexities raise concerns about unintended consequences and potential misuse. Consequently, the evolution of generative AI necessitates robust governance mechanisms to ensure responsible development and deployment. One crucial component of this governance framework is red teaming – a proactive approach to identifying and mitigating vulnerabilities and risks associated with these powerful technologies. Demystifying Red Teaming Red teaming is a cybersecurity practice that simulates real-world adversarial tactics, techniques, and procedures (TTPs) to evaluate an organization's defenses and…

21 May

Databricks

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Databricks is the second company in Generational’s late-stage company series. This was fun to write. As part of the research, I got the Lakehouse and Generative AI Fundamentals badges from Databricks Academy. Disclaimer: I have a financial interest in Databricks. Don’t take this as investment advice.In this deep dive, you’ll learn insights from conversations with many of Databricks’ customers and ex-employees. I want to thank Tegus for giving me access to their centralized expert call transcripts. With a platform as broad as Databricks, it is almost impossible to parse signal from the noise without primary research. If you’re curious about…

21 May

How LotteON built a personalized recommendation system using Amazon SageMaker and MLOps | Amazon Web Services

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This post is co-written with HyeKyung Yang, Jieun Lim, and SeungBum Shim from LotteON. LotteON aims to be a platform that not only sells products, but also provides a personalized recommendation experience tailored to your preferred lifestyle. LotteON operates various specialty stores, including fashion, beauty, luxury, and kids, and strives to provide a personalized shopping experience across all aspects of customers’ lifestyles. To enhance the shopping experience of LotteON’s customers, the recommendation service development team is continuously improving the recommendation service to provide customers with the products they are looking for or may be interested in at the right time.…