תחבורה ציבורית חינם. רכבות, אוטובוסים, הכל. אחרי מהפכת ״צדק תחבורתי״ עם 50% הנחה לפריפריה החברתית והגאוגרפית, נסיעות חינם לגילאי 67 וחיילים משוחררים, הנחות לצעירים ועוד. היעד הבא הוא תחבורה ציבורית חינם בכל הארץ. בוועידת האנרגיה והתשתיות של ערוץ 14 אמרתי היום כי הגודש עולה למשק 40 מיליארד ש״ח בשנה. בכהונתי העלינו את סבסוד התחבורה הציבורית ל־85%, ואני מתכוונת ללכת עם זה עד הסוף: פחות פקקים, פחות תאונות, פחות זיהום, פחות יוקר מחיה ויותר זמן לאזרחי ישראל.

קריאת מגילת אסתר בחניון התת קרקעי של דיזינגוף סנטר

First experience with EPIC’s AI Summaries “Generate Summary from Notes” This was early access in my health system in the outpatient setting, where it can generate a summary of what's gone on with the patient since my last visit. I'm overall pleased that Epic is headed in this direction, but so far my first impression was that it falls short in several major ways: 1. The latency essentially makes it unusable for me. It takes 40 seconds plus to generate a summary. 2. Summaries can only “see” notes. They don't see labs, they don't see imaging, and for a subspecialist that's severely limiting. Context is everything and that’s just not enough context. 3. The summary ends up showing me random snippets from my own previous note, and it's unclear how those are prioritized. They’re typically not the most important sentences. In the 40 seconds it took to render, I'm best off just pulling up my last note and reading it myself. Not quite ready for prime time, but a step in the right direction. If you have a clinician-facing AI product, you need to think very carefully about the user intent. And it should be FAST. It cannot slow people down. Has anyone tried this and found it useful?

🚨 Anthropic published a blog post saying Claude can modernize COBOL code and IBM instantly lost $31 billion in market cap. The post: "Legacy code modernization stalled for years because understanding legacy code cost more than rewriting it. AI flips that equation." That's IBM's entire business model. COBOL runs banks, insurance companies, government systems. Written in the 60s-70s. Nobody knows it anymore. Rewriting it costs millions. So companies pay IBM billions to maintain it forever. Anthropic just said "Claude can do it now." One blog post. $31 billion gone. This is what AI disruption actually looks like.