The 𝗧𝗵𝗶𝗻𝗸 𝗦𝗠𝗔𝗥𝗧 framework helps enterprises strike the right balance of accuracy, latency and ROI when deploying AI at AI factory scale. Learn more: https://
nvda.ws/41MTqTc
MARKET TRENDS
-
Think SMART Framework Balances AI Accuracy Latency ROI
By
–
-
Blackwell Delivers 4x Performance and 10x Profit Gains
By
–
𝗥eturn On Investment driven by performance Performance per watt per $ = profit. Moving from Hopper to Blackwell delivers 4× more perf and up to 10× profit within the same power budget.
-
Smart Inference Deployment: Scaling AI Across Enterprise Systems
By
–
Deploying AI at scale requires you to 𝗧𝗵𝗶𝗻𝗸 𝗦𝗠𝗔𝗥𝗧 about inference: 𝗦cale and complexity 𝗠ulti-dimensional performance
𝗔rchitecture & software
𝗥OI driven by performance
𝗧echnology ecosystem & install base Let’s break it down -
ByteDance and Alibaba Launch New AI Products
By
–
Yes. That too is from China by ByteDance. And this is a new one from Alibaba.
-
Blackwell delivers 4x performance within same power budget
By
–
𝗥eturn On Investment driven by performance Performance per watt per $ = profit. Moving from Hopper to Blackwell delivers 4× more perf and up to 10× profit within the same power budget.
-
Google Imagen 4 Released: Three Models Pricing and Performance
By
–
Google’s Imagen 4 is here, but is it worth your time? 🎨✨
— Louis-François Bouchard 🎥🤖 (@Whats_AI) 21 août 2025
What’s new
• Family of 3 models:
– Imagen 4 Fast → $0.02 per image, ~2.7s latency (10x faster than Imagen 3)
– Imagen 4 → $0.04 per image
– Imagen 4 Ultra → $0.06 per image, ~10s latency, higher detail (up to 2K… pic.twitter.com/HkbwHzEBa5Google’s Imagen 4 is here, but is it worth your time? What’s new • Family of 3 models: – Imagen 4 Fast → $0.02 per image, ~2.7s latency (10x faster than Imagen 3) – Imagen 4 → $0.04 per image – Imagen 4 Ultra → $0.06 per image, ~10s latency, higher detail (up to 2K
-
AI Failing at Majority of Companies Using It Study
By
–
AI Is Failing at an Overwhelming Majority of Companies Using It, MIT Study Finds:
-
Reasoning Models Token Price Beyond Surface Analysis
By
–
De la gráfica anterior hay que tener en cuenta que hablamos del precio por token, y sabemos que los modelos razonadores exprimen sus capacidades generando más tokens… así que bueno, tomad la parte del precio como un indicador pero que no cuenta la historia completa.
-
AI Model Power Increases While Costs Decrease Year-Over-Year
By
–
Por visualizar el cuadrante inteligencia vs precio, el punto que marco es el modelo más potente que teníamos hace justo un año. Todos los demás, más baratos, más potentes… es lo que se ha logrado en los último 12 meses.
-
AI Gap: Workers’ Expectations vs Current Capabilities Study
By
–
A study conducted by @StanfordHAI and @DigEconLab scholars revealed a concerning gap between what workers want from AI and the reality of its current capabilities.