Created by Bjørn Karmann, Paragraphica is a camera that utilizes location data and AI to visualize a “photo” of a specific place and moment. The camera exists both as a physical prototype and an online camera that you can try. — Read More
Monthly Archives: May 2023
350+ industry leaders sign Statement on AI Risk
Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war. — View the List of Signatories
#singularityDon’t Get Distracted by the Hype Around Generative AI
Tech bubbles are bad information environments.
Technology bubbles can pose difficult quandaries for business leaders: They may feel pressure to invest early in an emerging technology to gain an advantage over competitors but don’t want to fall for empty hype. As we enter a period of greater economic uncertainty and layoffs in multiple industries, executives are grappling with questions about where to cut costs and where to invest more.
The rapidly developing field of artificial intelligence and machine learning poses a particular challenge to business decision makers. Investments in proven predictive models are increasingly seen as sound and are expected to drive an increase in spending on AI from $33 billion in 2021 to $64 billion in 2025. But further out on the cutting edge, generative AI is sparking a huge amount of noise and speculation. — Read More
AI Coding Tools
Coding is arguably the single best application of large language models (LLMs) to date! The market for AI Coding tools is booming, with 100+ tools and competition across Big Tech, established Unicorns and emerging AI-native startups. Read on for an introduction. [1/13] — Read More
Introducing Charlotte AI, CrowdStrike’s Generative AI Security Analyst: Ushering in the Future of AI-Powered Cybersecurity
… Charlotte AI is a new generative AI security analyst that uses the world’s highest-fidelity security data and is continuously improved by a tight feedback loop with CrowdStrike’s industry-leading threat hunters, managed detection and response operators, and incident response experts. This is the first offering built using our Charlotte AI engine and will help users of all skill levels improve their ability to stop breaches while reducing security operations complexity. Customers can ask questions in plain English and dozens of other languages to receive intuitive answers from the CrowdStrike Falcon platform.
Currently available in private customer preview, Charlotte AI initially addresses three common use cases:
- Democratizing Cybersecurity – Every User Becomes a Power User: With Charlotte AI, everyone from the IT helpdesk to executives like CISOs and CIOs can quickly ask straightforward questions such as “What is our risk level against the latest Microsoft vulnerability?” to directly gain real-time, actionable insights, drive better risk-based decision making and accelerate time to response.
- Elevate Security Analyst Productivity with AI-Powered Threat Hunting: Charlotte AI will empower less experienced IT and security professionals to make better decisions faster, closing the skills gap and reducing response time to critical incidents. New security analysts, such as a Tier 1 member of a SOC, will now be able to operate the CrowdStrike Falcon platform like a more advanced SOC analyst.
- The Ultimate Force Multiplier for Security Experts: Charlotte AI will enable the most experienced security experts to automate repetitive tasks like data collection, extraction and basic threat search and detection while making it easier to perform more advanced security actions. It will also accelerate enterprise-wise XDR use cases across every attack surface and third-party product, directly from the CrowdStrike Falcon platform. Hunting and remediating threats across the organization will be faster and easier by asking simple natural language queries.
#cyber
Winning the AI Products Arms Race
Roughly every decade, technology makes a giant leap that erases the old rules and wipes out our assumptions. The Internet. Mobile. Video. Blockchain. Like clockwork, companies and creators begin a mad race to make money off the next big thing, burning through ungodly sums of cash in the process.
Unless you’ve been living off the grid for the past year, it’s clear that the next big thing is artificial intelligence (AI). Early in 2023, ChatGPT is the tool du jour. Spend a few minutes on Twitter and you’ll see people gushing over its ability to write screenplays, debug code, or tell you how to make dairy-free mac and cheese.
Giving anybody with WiFi the ability to churn out unlimited amounts of (mostly) accurate information on demand is a sci-fi level feat. But how can companies leverage the technology behind GPT — and AI in general — to solve substantive problems and expand their product market fit?
That’s the million (or trillion) dollar question. — Read More
Production AI systems are really hard
No, AGI isn’t going to take over every social system when GPT5 comes out
I don’t talk much about this – I obtained one of the first FDA approvals in ML + radiology and it informs much of how I think about AI systems and their impact on the world.
… Geoffrey Hinton was one of the loudest voices decrying the decline of radiology 5 years, and now he’s crying fear for new AI systems.
There’s a lot to unpack for both why Geof was wrong, and why his future predictions should not be taken seriously either. — Read More
Yann LeCun, Chief AI Scientist at Meta AI: From Machine Learning to Autonomous Intelligence
Combining Text-to-SQL with Semantic Search for Retrieval Augmented Generation
In this article, we showcase a powerful new query engine ( SQLAutoVectorQueryEngine ) in LlamaIndex that can leverage both a SQL database as well as a vector store to fulfill complex natural language queries over a combination of structured and unstructured data. This query engine can leverage the expressivity of SQL over structured data, and join it with unstructured context from a vector database. We showcase this query engine on a few examples and show that it can handle queries that make use of both structured/unstructured data, or either.
Check out the full guide here: https://gpt-index.readthedocs.io/en/latest/examples/query_engine/SQLAutoVectorQueryEngine.html.
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Rick's Cafe AI 