It's a *lot* more than adjusting the coefficients of your PID controllers.
Building a model of your own dynamics is acquiring a kind of knowledge, but it's relatively simple.
However, learning a model of the world and of your possible interactions with it is fiendishly complex.
SYSTEMS
-
Learning World Models Beyond PID Controller Tuning
By
–
-
Balancing Speed and Accuracy in Dynamic AI Model Design
By
–
The challenge is to design a model that preserves accuracy amidst dynamic situations, potential threats, and numerous queries, by balancing speedy results with precise forecasts, since users appreciate timely responses, tolerating minor inaccuracies.
-
Vector Databases Replaced by Single Transformer Models
By
–
prediction: every vector database will eventually be replaced with a single transformer a row for every individual datapoint is so old-school, feels outdated what would be better: a single differentiable blob, something that “knows” about all your data and can chat about it
-
Hybrid AI System Combining Search, Reasoning and Generation
By
–
Imagine a chatbot and a vector db had a baby this thing can do search, sure, but it’s much more capable: can do search, reasoning, and generation, all at once
-
Network Coverage and Real-Time Requirements for AGI Development
By
–
Or for phone coverage to always work so wi fi / internet was available or AGI is dead. Or real time AGI.
-
Japanese Insurer Uses AI System for Claims Response Automation
By
–
I'm remembering a particular Japanese insurance company here, which debuted an AI system to enforce the invariant that, if you mail them a claim, you get a response that same month. Now plausibly you might say "That sounds a lot like pedestrian workflow automation and SQL."
-
Gap Between AI Description and Physical Task Execution
By
–
There is a huge gap between regurgitating a description of a physical activity and being able to accomplish it.
-
DeepSpeed-FastGen: 2.3x Throughput Improvement for LLM Serving
By
–
Introducing DeepSpeed-FastGen V/ @MSFTDeepSpeed **************
Serve LLMs and generative AI models with
– 2.3x higher throughput
– 2x lower average latency – 4x lower tail latency
w. Dynamic SplitFuse batching Auto TP, load balancing w. perfect linear scaling, plus -
Infrastructure Outages and Tunnels: Critical Concerns Ahead
By
–
Yikes! Outages, tunnels etc are going to be a problem…
-
Real-time AI Models in Business Decision-Making Processes
By
–
It often involves applying live models within an organization’s decision-making processes-for example, real-time personalization web page, product recommender system, or scoring of marketing leads.