How finance teams are putting AI to work today
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @HaroldSinnott @fogoros @iainljbrown @NandoDF @katecrawford @drhassanrashidi @YuHelenYu
ENTERPRISE AI
-
How Finance Teams Deploy AI Today
By
–
-
GLM-4.7 Live on Cerebras: Frontier Coding Intelligence
By
–
GLM-4.7 from @Zai_org is live on Cerebras!
— Cerebras (@cerebras) 8 janvier 2026
– Frontier intelligence for coding, tool-driven agents, and multi-turn reasoning
– Record coding speed: ~1,000 tokens per second (up to 1,700 TPS for other uses)
– Strong price-performance: ~10x higher than Sonnet 4.5 pic.twitter.com/HGTcVvhZVQGLM-4.7 from @Zai_org is live on Cerebras! – Frontier intelligence for coding, tool-driven agents, and multi-turn reasoning
– Record coding speed: ~1,000 tokens per second (up to 1,700 TPS for other uses)
– Strong price-performance: ~10x higher than Sonnet 4.5 -
AI Transforms Financial Services Workflows for Better Customer Outcomes
By
–
Embedding AI into everyday workflows delivers a simple payoff: faster, quicker, better outcomes for customers. That’s where Financial Services is heading next. Watch The Future of AI in Financial Services to hear how leaders are making it real:
-
Bad Data Costs: Engineering Hours and Industrial Downtime
By
–
The costs of bad data include wasted engineering hours and unplanned downtime for industrial operators. Missed opportunities to prevent major failures add to the impact. Full article: https://
buff.ly/WIeOyPE @InfluxDB #sponsored #influx_iiot #CES2026 -
AI Industry Leadership and Partnerships Define 2025
By
–
2025 was an important year when different industries with different missions all focused on one thing: AI that actually works. Our biggest moments were about deep partnerships that translated to industry leadership, bold conversations and best practices. Here's to 2026! pic.twitter.com/9FpcOR2PAu
— Domino Data Lab (@DominoDataLab) 8 janvier 20262025 was an important year when different industries with different missions all focused on one thing: AI that actually works. Our biggest moments were about deep partnerships that translated to industry leadership, bold conversations and best practices. Here's to 2026!
-
Jamba2 Outperforms Competing Models in Enterprise Reliability
By
–
2/4 Grounding + instruction following
Jamba2 outperforms peer models from @MistralAI and @alibaba_cloud on IFBench, IFEval, and FACTS, core indicators of enterprise reliability. -
Jamba2: Open Source Model for Enterprise Reliability
By
–
1/4 Introducing Jamba2, a memory-efficient open source model family built for total enterprise reliability and steerability.
-
5G Standalone and Network Slicing Enable Real-Time Content Creation
By
–
A clear example of how 5G Standalone and network slicing move from infrastructure concepts to concrete value, because reducing latency and friction in the field changes how content is created, shared, and experienced in real time. @TMobileBusiness
-
AI Glasses Provide Real-Time On-the-Job Training
By
–
AI Glasses teach in real time. While doing the job.
-
Context Breakdown: The Hidden Challenge in AI System Reliability
By
–
Most AI systems don’t fail because of bad prompts.
They fail because context breaks at scale. If you’re building AI agents, LLM workflows, copilots, or automation, this is the layer that quietly decides whether your system is reliable or unpredictable. We’re hosting a 5-hour,