“The world is shifting from building AI models to renting AI intelligence.”. @manuaero, CEO of @labelbox, explains how his company captured this opportunity by rethinking its business from the ground up:

Today was my last day at Labelbox - I learned a ton, made friends and lifelong professional connections, and can definitely say that it's going to be exciting to watch them grow! . In terms of next steps, I start my new role shortly - any guesses based on the picture below? 🖼

I keep seeing teams wrestling with the same data annotation problem: Label Studio, Scale Nucleus, Labelbox, CVAT are great but. for the labeling itself and visualization but the pipeline around it is a manual, script-heavy nightmare. What if your annotation workflow was

Here are 6 beginner-friendly data jobs to kick-start your data career!. 1️⃣ Data Annotation Specialist. Label images, text, or audio for AI models. No code needed. 🛠️ Tools: Labelbox, Prodigy, Excel. 🔗 Link to jobs: 2️⃣ Reporting Analyst. Create

Google cuts ties with Scale AI after Meta takes 49% stake sparking major shake-up in AI labeling market:. • Google shifting $200M annual labeling spend away from Scale. • Microsoft, xAI, OpenAI also backing off. • Competitors Labelbox & Handshake already seeing demand

Gemini 2.5 Pro tops Labelbox's Agentic Search Benchmark. You can ground Gemini with Google Search on Vertex AI to get accurate, up to date results. We are always doing more to improve in this space.

スタートアップ企業の65％は、「創業者チーム内の人間関係が原因で失敗」している。a16zやSoftbankも出資するLabelboxの創業者達は、共通のプロコーチを創業直後に持ち、価値観・精神性の認識を合わせた。「その場で判断できるよう、共同創業者との深い信頼関係は必然。」

👑 We’re #1! Sonic-2 leads @Labelbox’s Speech Generation Leaderboard topping out in speech quality, word error rate, and naturalness. Build your real-time voice apps with the 🥇 best voice AI model. ➡️

The @JoinSapien has many rivals. Big companies like Google and Amazon already do data labeling. Vertex AI and SageMaker are big systems. There are also tools like Labelbox and Dataloop. They are good at labeling pictures. Appen and Scale AI work with millions of people. But

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Pricing Data in the AI Era: Labelbox’s Challenge. @alex digs into how @Labelbox thinks about pricing its data services. Key takeaways:. In the SaaS days, Labelbox charged based on platform usage, but entering data services means pricing per labeled data point—or the value that

Time-to-value is critical for PLG. In our latest case study, John Vega (Director of Product Support at Labelbox) shared:. “I originally discovered Kraftful by searching online after manually exporting support tickets into ChatGPT without any success. I initially tried a few

We’re thrilled to welcome Ken Olofsen as Cortex’s new VP of Marketing! 💜. Ken’s led GTM at Atlassian, Semmle (GitHub), and Labelbox. and now he’s betting on Cortex. Why? Read his take → Join us → 🚀

Still stitching tools together to build and ship AI?.You’re not alone. Most platforms only solve part of the workflow — but not the full pipeline. Let’s break it down:. 📦 Labelbox/V7? Great for labeling — but no automation or GPU flexibility. 🔁 n8n/Make? Good at general

@CanadaRefer @avilajujbs Alignerr is a legit platform by Labelbox for experts to earn by training AI models via data tasks. Their referral program pays $125 per successful referral who passes assessments. However, reviews are mixed: many report account deactivations, unpaid work, and poor support (e.g.,.

Smarter data labeling with Labelbox! 🚀. #Labelbox #AItools #DataAnnotation. CONTACT US: 9004527361 . @msanjeet2u

EVERY FAMOUS MAN. @labelbox @retool . Fame and infamy are closely related. #MondayMotivaton #PictureOfTheDay #InArt #AiaClips #Live2D #Trailblazer #OC

I dove deep into Labelbox’s purpose — transforming raw data into actionable AI training sets. This revealed a core narrative: organization, clarity, and intelligence, which became the foundation for visual storytelling. 🧵Here's how went about the redesign of Labelbox's logo.