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Breaking Down the Complex Language of AI Artificial intelligence is changing the world, and simultaneously inventing a whole new language to describe how it’s doing it. Spend five minutes reading about AI and you’ll run into LLMs, RAG, RLHF, and a dozen other terms that can make even very smart people in the tech world feel insecure. This glossary is our attempt to fix that. We update it regularly as the field evolves, so consider it a living document, much like the AI systems it describes. Artificial General Intelligence (AGI) Artificial general intelligence, or AGI, is a nebulous term. But it generally refers to AI that’s more capable than the average human at many, if not most, tasks. OpenAI CEO Sam Altman once described AGI as the “equivalent of a median human that you could hire as a co-worker.” Meanwhile, OpenAI’s charter defines AGI as “highly autonomous systems that outperform humans at most economically valuable work.” Google DeepMind’s understanding differs slightly from these two definitions; the lab views AGI as “AI that’s at least as capable as humans at most cognitive tasks.” Confused? Not to worry — so are experts at the forefront of AI research. AI Agent An AI agent refers to a tool that uses AI technologies to perform a series of tasks on your behalf — beyond what a more basic AI chatbot could do — such as filing expenses, booking tickets or a table at a restaurant, or even writing and maintaining code. However, as we’ve explained before, there are lots of moving pieces in this emergent space, so “AI agent” might mean different things to different people. Infrastructure is also still being built out to deliver on its envisaged capabilities. But the basic concept implies an autonomous system that may draw on multiple AI systems to carry out multistep tasks. API Endpoints Think of API endpoints as “buttons” on the back of a piece of software that other programs can press to make it do things. Developers use these interfaces to build integrations — for example, allowing one application to pull data from another, or enabling an AI agent to control third-party services directly without a human manually operating each interface. Most smart home devices and connected platforms have these hidden buttons available, even if ordinary users never see or interact with them. As AI agents grow more capable, they are increasingly able to find and use these endpoints on their own, opening up powerful — and sometimes unexpected — possibilities for automation. Chain-of-Thought Reasoning Given a simple question, a human brain can answer without even thinking too much about it — things like “which animal is taller, a giraffe or a cat?” But in many cases, you often need a pen and paper to come up with the right answer because there are intermediary steps. For instance, if a farmer has chickens and cows, and together they have 40 heads and 120 legs, you might need to write down a simple equation to come up with the answer (20 chickens and 20 cows). Coding Agent This is a more specific concept that an “AI agent,” which means a program that can take actions on its own, step by step, to complete a goal. A coding agent is a specialized version applied to software development. Rather than simply suggesting code for a human to review and paste in, a coding agent can write, test, and debug code autonomously, handling the kind of iterative, trial-and-error work that typically consumes a developer’s day. Compute Although somewhat of a multivalent term, compute generally refers to the vital computational power that allows AI models to operate. This type of processing fuels the AI industry, giving it the ability to train and deploy its powerful models. The term is often a shorthand for the kinds of hardware that provides the computational power — things like GPUs, CPUs, TPUs, and other forms of infrastructure that form the bedrock of the modern AI industry. Deep Learning A subset of self-improving machine learning in which AI algorithms are designed with a multi-layered, artificial neural network (ANN) structure. This allows them to make more complex correlations compared to simpler machine learning-based systems, such as linear models or decision trees.

The AI-Driven Workforce Transformation at CloudflareCloudflare has joined a growing list of tech companies reporting increased revenue alongside massive layoffs, with the internet security and performance services provider announcing a 20% workforce reduction (1,100 employees) during its first quarter 2026 earnings report. The company attributes both trends to its adoption of artificial intelligence, marking the first mass layoff in Cloudflare's 16-year history.Record Revenue Amid Workforce ReductionsDespite the significant job cuts, Cloudflare reported impressive financial results for the first quarter of 2026, with quarterly revenues reaching $639.8 million—a 34% year-over-year increase and the highest single quarter in the company's history. However, the company still posted a loss of $62.0 million, compared to a $53.2 million loss in the year-ago quarter. The widening loss, even as revenue surged, highlights a familiar paradox: Cloudflare is growing fast but has yet to achieve consistent profitability.Financial Metrics and Growth IndicatorsThe company's positive financial indicators include over $2.5 billion in "remaining performance obligations" (RPO), representing a 34% year-over-year growth. RPO measures revenue under contract but not yet delivered, and has become a key metric for investors. Despite the losses, Cloudflare's financial performance demonstrates strong market demand for its services, even as the company undergoes significant internal restructuring.AI as the Catalyst for Organizational ChangeCloudflare's CEO Matthew Prince emphasized that the workforce reductions were not a cost-cutting measure but a direct result of AI adoption. "Today's actions are not a cost-cutting exercise or an assessment of individuals' performance; they are about Cloudflare defining how a world-class, high-growth company operates and creates value in the agentic AI era," Prince and co-founder Michelle Zatlyn stated in a blog post.Productivity Revolution Through AI ImplementationPrince described an internal productivity revolution that began in November 2025, when teams started experiencing massive efficiency gains. "Team members that were two, 10, even 100 times more productive than they had been before," he said, comparing the shift to "going from a manual to an electric screwdriver." Cloudflare's AI usage has increased by more than 600% in the last three months alone, with employees across all departments running thousands of AI agent sessions daily.Technical Implementation of AI in DevelopmentThe company has integrated AI deeply into its development processes, with virtually the entire R&D; team now using Cloudflare's Workers platform—including its vibe coding feature. Notably, 100% of the code produced and deployed for Cloudflare's products is "now reviewed by autonomous AI agents." This technical transformation has reduced the need for traditional support roles, as AI-powered employees require fewer support staff to maintain productivity.Future Workforce Strategy and Hiring PlansDespite the significant layoffs, Cloudflare plans to continue hiring employees who can effectively leverage AI tools. "We'll continue to hire people, and we'll continue to invest in them because the people that are embracing these tools are just so much more productive than we'd ever seen before," Prince stated. The company anticipates having more employees in 2027 than at any point in 2026, suggesting a strategic realignment rather than a simple workforce reduction.Industry-Wide Pattern of AI-Driven RestructuringThe pattern Cloudflare describes—using AI gains as justification for workforce reductions during revenue growth—is becoming increasingly common across the tech industry. Companies like Meta, Microsoft, and Amazon have reported similar trends, raising questions about whether this reflects true structural transformation or serves as convenient cover for cost discipline. As Prince put it when asked about the deep cuts after a strong quarter: "Just because you're fit doesn't mean you can't get fitter."

The Enterprise AI Gold Rush The enterprise AI market is witnessing a surge in deals and investments, with several companies making significant moves to capitalize on the growing demand for AI solutions. This week, Anthropic and OpenAI announced new joint ventures targeting enterprise AI deployment, while SAP invested $1B in German AI startup Prior Labs. Key Players and Deals Anthropic and OpenAI: Announced new joint ventures targeting enterprise AI deployment SAP: Invested $1B in German AI startup Prior Labs xAI: Entered into a compute arrangement with Anthropic The Acquisition Landscape With these moves, it's becoming clear that startups building enterprise tools are likely acquisition targets. The enterprise AI market is attracting significant attention, and companies are positioning themselves for a potential IPO season. What's Next? As the enterprise AI market continues to evolve, we can expect to see more deals and investments in the coming months. The Equity podcast hosts discuss these developments and what they mean for the future of AI in the enterprise space. Stay Up-to-Date To stay informed about the latest developments in the enterprise AI space, subscribe to the Equity podcast on YouTube, Apple Podcasts, Overcast, Spotify, and follow Equity on X and Threads at @EquityPod.

The Rise of Self-Driving Trucks The autonomous vehicle industry has been on the cusp of breakthroughs for over a decade. However, Aurora, a self-driving truck company co-founded by Chris Urmson, has made significant strides in recent times. Aurora's Scaling Plans Aurora started commercial driverless operations last April and is now scaling up from a handful of trucks to hundreds this year. This development marks a significant milestone in the company's journey and the broader self-driving truck industry. The Road to Commercialization Aurora's journey began with DARPA challenges and initial forays into driverless trucks hauling freight between Dallas and Houston. The company's focus on physical AI sets it apart from the current LLM (Large Language Model) boom in the tech industry. Expert Insights Chris Urmson, co-founder and CEO of Aurora, shared his insights on the long road from lab to highway in a conversation with Rebecca Bellan at the HumanX conference in San Francisco. The Future of Self-Driving Technology As Aurora continues to scale its operations, the company is poised to play a significant role in shaping the future of self-driving technology. The industry's progress will likely be closely watched by investors, policymakers, and consumers alike. Staying Up-to-Date For the latest updates on Aurora and the self-driving truck industry, listeners can tune into TechCrunch's Equity podcast on YouTube, Apple Podcasts, Overcast, Spotify, and other platforms.

The Final Hours: 50% Off Second Pass to TechCrunch Disrupt 2026 Time is running out to take advantage of the 50% off offer for a second pass to TechCrunch Disrupt 2026. Today, May 8th, is the last day to register and secure your spot at the premier tech conference in San Francisco. Unlock the Full Potential of Disrupt 2026 Attending Disrupt with a partner, co-founder, or colleague can significantly enhance your experience. You'll gain more insights, compare notes in real-time, and make informed decisions. The 50% off offer for a second pass is a unique opportunity to bring someone along and maximize your time at the conference. What You'll Gain at Disrupt 2026 Access to over 250 sessions, covering real-world playbooks and industry trends Opportunities to connect with key players, investors, and innovators Enhanced networking capabilities with a second pass The Cost of Waiting Missing this offer means more than just paying a higher price. It means attending the conference with a limited perspective, choosing between sessions, and processing information without the benefit of real-time discussion and feedback. Act Now and Save Don't miss your chance to save up to $410 on your pass and get 50% off a second pass. Register now and secure your spot at Disrupt 2026. The offer ends tonight at 11:59 p.m. PT.

The End of Swiping on Bumble Bumble is bidding farewell to the swipe, a feature that defined dating apps in the 2010s. In an interview with Axios, Bumble CEO Whitney Wolfe Herd confirmed that the app will revamp its platform, introducing a new feature she believes will be revolutionary for the category. Disappointing Quarters Prompt Change The decision to overhaul the app comes after several disappointing quarters, including a 21% decline in paid users to 3.2 million in the first quarter, down from 4 million last year. Wolfe Herd framed the decline as a deliberate choice to prioritize quality over quantity, focusing on engaged and well-intentioned members. The Future: AI-Driven Relationships? Bumble is expected to lean into AI technology, having already developed an AI dating assistant called Bee. Wolfe Herd has expressed enthusiasm for AI's potential to supercharge relationships, even suggesting that personal AI bots could date other AI bots on behalf of users. The Impact on Users and the Industry The overhaul, expected to launch in the last quarter of this year, signals a significant shift in Bumble's strategy. While it's unclear whether the new approach will attract younger users, who are trending more negative toward overt AI features, the company's move reflects a broader industry evolution. The Prediction: A New Era for Dating Apps As Bumble prepares to say goodbye to swiping, the dating app landscape is poised for a transformation. With Gen Z users increasingly skeptical of AI-driven features, Bumble's success will depend on its ability to balance innovation with user preferences. The question remains: will this bold move revitalize the app, or will it further exacerbate the dating app malaise?

The Deadline Approaches: Startup Battlefield 200 Applications Close May 27 Startup Battlefield 200 applications are open, but only for three more weeks. Apply by May 27 for your shot at VC access, global visibility, TechCrunch coverage, $100,000 equity-free, and more opportunities for major scaling impact. Who Should Apply: Pre-Series A Founders and Ambitious Startups Pre-Series A founders — and anyone who knows a startup worth backing — this is your reminder: The deadline is approaching fast, and the strongest contenders are already entering the arena. If your startup has been nominated, don’t wait. Complete your application now before the window closes. Know a startup that deserves to step into the spotlight? Nominate them now to give them time to complete the application by the deadline. The Opportunity: A Platform for Growth and Visibility This is not just another pitch competition. Startup Battlefield 200 puts you on the main stage at TechCrunch Disrupt 2026 in front of 10,000+ attendees, top-tier investors, media, and the global TechCrunch audience. You are competing live, getting direct VC feedback, and proving your company belongs among the next breakout startups. What We’re Looking For: Innovative and Ambitious Startups We’re looking for ambitious early-stage startups building innovative, potentially category-defining products. Applications are open globally across every industry. Most selected companies are pre-Series A, though select Series A startups may qualify case by case. A functional MVP and clear product demo are required. Most importantly, we’re looking for founders building with vision, execution, and real market impact. A Proven Track Record: Launchpad for Successful Startups This is the same launchpad where companies like Dropbox, Discord, Fitbit, Trello, and Mint gained early momentum. Thousands apply every year. Only 200 are selected. Just 20 finalists pitch live on the Disrupt Stage. One startup takes the crown. The Benefits: High ROI Opportunity for Early-Stage Founders Selected startups receive one of the highest ROI opportunities available to early-stage founders. It’s free to apply, and the potential return — from investor exposure to media coverage and customer growth — can create real scaling impact. The Final Push: Don’t Miss the Deadline Applications close May 27. The founders who break through are not waiting until the final hour — they are already making their move. If you are building something category-defining, or know a founder who is, now is the time to step forward. Nominate your startup — or one that deserves the spotlight — and complete your application before the deadline runs out.

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The Lead At the Milken Institute Global Conference, leaders from across the AI supply chain gathered to discuss the current state and future of artificial intelligence. They touched on various challenges, including chip shortages, energy constraints, and the potential for new AI architectures. The Bottlenecks in AI Development The discussion highlighted several bottlenecks in AI development. Christophe Fouquet, CEO of ASML, noted that despite efforts to accelerate chip manufacturing, the market will likely remain supply-limited for the next two to five years. Francis deSouza, COO of Google Cloud, pointed out the immense demand for AI infrastructure, with Google Cloud's revenue growing 63% and its backlog nearly doubling to $460 billion. The Data and Energy Constraints Qasar Younis, co-founder and CEO of Applied Intuition, emphasized that the bottleneck for his company is not silicon but data gathered from the real world, which is essential for training physical AI models. The energy required to power AI infrastructure is also a significant concern. deSouza mentioned that Google is exploring data centers in space to address energy constraints, although this comes with its own set of challenges. New AI Architectures and Their Implications Eve Bodnia, founder of Logical Intelligence, discussed a different approach to AI, focusing on energy-based models (EBMs) that aim to understand the underlying rules of data, similar to human brain function. This approach could be particularly useful for applications requiring an understanding of physical rules, such as chip design and robotics. The Future of AI: Agents, Guardrails, and Trust Dmitry Shevelenko, chief business officer of Perplexity, talked about the evolution of its search product into a 'digital worker' called Perplexity Computer. This tool is designed to act as a staff that a knowledge worker can direct, raising questions about control and security. Shevelenko emphasized the importance of granularity in permissions and actions to ensure trust and security. The Geopolitical and Generational Impact The discussion also touched on the geopolitical implications of physical AI and its impact on national sovereignty. Younis noted that physical AI manifests in the real world in ways that governments can't ignore, leading to questions about safety, data collection, and control. Regarding the impact on the next generation, the panelists were optimistic, highlighting the potential for AI to help address significant problems and unleash new levels of creativity and opportunity.