Boston Children’s uses AI to unlock new diagnoses
Boston Children’s Hospital uses OpenAI technology to improve patient care, reduce operational burden, and help diagnose more than 40 rare disease cases.
Like
0
Liked
Liked
digitado
About digitado
Posts by :
Quiz: Python’s assert: Debug and Test Your Code Like a Pro
In this quiz, you’ll test your understanding of Python’s assert: Debug and Test Your Code Like a Pro. By working through this quiz, you’ll revisit how assertions help you debug, test, and document your code, when to disable them in production, and which common pitfalls to avoid. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more […]
Like
0
Liked
Liked
The Real Python Podcast – Episode #297: Improving Python Through PEPs and Protocols
Have you ever been confused by the naming of modules you’re importing from a package? Is there a standard way to organize and name your Python virtual environments? This week on the show, Brett Cannon returns to discuss the Python Enhancement Proposals (PEPs) he’s been working on recently. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn […]
Like
0
Liked
Liked
Connectivity of Networks Modeled by Weighted Graphs
A graph G=(V,E) together with a positive real-valued weight-function w:V→R+ or w:E→R+ is called a weighted graph and is denoted by (G;w). In this paper, we introduce the concepts of connectivity, edge-connectivity, and restricted edge-connectivity for a weighted graph (G;w), and we prove general bounds analogous to those in the unweighted case. Furthermore, we study the connectivity and edge-connectivity of the line graph and the P2-path graph of a weighted graph, establishing upper and lower bounds for each […]
Like
0
Liked
Liked
Entropy Estimation in Cluster Graphs
Probabilistic graphical models (PGMs) provide a powerful framework for modelling complex systems, but inference over loopy graphs requires approximate methods whose accuracy depends on how factors are clustered in the graphical representation. Existing factor clustering methods rely on the number of variables in a cluster as a proxy for memory cost and informational content—a loose upper bound that leads to suboptimal merging decisions. We address this limitation by proposing an efficient algorithm for estimating the joint entropy of […]
Like
0
Liked
Liked
Resource-Efficient Continual Learning for Medicinal Plant Identification: A Periodic Retraining Approach for Edge-Deployed Agricultural IoT Applications
Smartphone-based plant identification increasingly serves as the edge tier of agricultural Internet of Things (IoT) systems, where models must adapt to crowdsourced data under bandwidth, memory, and energy constraints. No prior work has systematically investigated continual learning at the scale of thousands of fine-grained medicinal plant species, nor how retraining frequency affects the cost–performance trade-off in an IoT model-lifecycle setting. We evaluate three continual learning strategies—naïve fine-tuning, experience replay, and Learning without Forgetting—under periodic retraining schedules (updating every […]
Like
0
Liked
Liked
Anthropic releases Claude Opus 4.8
Anthropic has released Claude Opus 4.8, an upgrade to Claude Opus 4.7 that the company says brings improved results for coding, agent work, reasoning, and knowledge work. The platform can be used through claude.ai, Claude Code and the Claude API, with the API name claude-opus-4-8. The company has also altered some of the details of its product line-up. Users of claude.ai and Cowork can set the amount of effort Claude applies to a response – essentially, affecting the […]
Like
0
Liked
Liked
Full-Stack Data Scientists for the Agentic Coding World
Author(s): Michael Shapiro MD MSc Originally published on Towards AI. The Next Evolution of Data Teams For years, building data products required a chain of specialists: data engineers, data scientists, software engineers, ML engineers, MLOps teams, and product managers. This specialization enabled organizations to tackle increasingly complex problems, but it also introduced handoffs, dependencies, and slower feedback cycles. (If you’re not a Medium Member, read it for free here). After the introduction, the article explains why agentic coding […]
Like
0
Liked
Liked
Inside Palantir AIP: How the World’s Most Controversial AI Platform Actually Works
Author(s): Akash Dogra Originally published on Towards AI. Inside Palantir AIP: How the World’s Most Controversial AI Platform Actually Works Ontology-Augmented Generation, Apollo’s air-gapped deployments, and the k-LLM routing architecture — a deep technical teardown. This photograph taken on January 19, 2023 shows a woman walking past the logo of US big data analytics software company Palantir Technologies during the World Economic Forum (WEF) annual meeting in Davos. (Photo by Fabrice COFFRINI / AFP via Getty Images) The […]
Like
0
Liked
Liked
What Claude Opus 4.8 Actually Changes If You’re Building Agents
Author(s): Rajesh Vishnani Originally published on Towards AI. What Claude Opus 4.8 Actually Changes If You’re Building Agents I’ve been building AI agents for long enough now to have developed a healthy reflex: whenever a new frontier model drops, my first question isn’t “is it smarter?” It’s “does it change the shape of the code I have to write?” Most releases don’t. They nudge a benchmark, shave a few cents off a token, and the agent loop I […]
Like
0
Liked
Liked