🎗️ Uri Goren

Exploring the e in Health |Head of innovation @ Meir Medical Center | A digital health enthusiast and blogger | A family man | opinions are my own

[SpaceX @SpaceX]

SpaceX has exercised the option to acquire @cursor_ai in an all-stock transaction with the goal of building the world’s most useful AI models.

For the past few months, SpaceXAI has been jointly training a model with Cursor, which will be released in Cursor and Grok Build soon.

We look forward to working closely with the Cursor team to advance our frontier AI capabilities

[🎗️ Uri Goren @urigoren]

@JakeFleshner Vibe adherence

[🎗️ Uri Goren @urigoren]

@Bnayap אולי התגובות, אבל המציאות של חרם על הר׳י זה הרסני ברמה הלאומית

[🎗️ Uri Goren @urigoren]

הלנצט תמיד היה הירחון הפחות ידידותי לישראל. אבל התגובות השמחות של ישראלים (באופן מוזר משני צידי המפה הפוליטית) מפחידות לא פחות

[עידו וולף @IdoWolf1]

מפחיד ממש.
מאמר בלנצט, אחד משני העיתונים הרפואיים החשובים בעולם, מסקר קריאות להחרמת ההסתדרות הרפואית הישראלית.
המאמר מביא גם את תגובת הר״י, אבל עצם העלאת הנושא כאן נותנת לגיטימציה לקריאות לחרם.

https://t.co/VEQb98o4zO

[🎗️ Uri Goren @urigoren]

@SagivElmaleh @morad

[Sagiv @SagivElmaleh]

שלחו לי אתר נחמד שמיפה את כל (?) קרנות הון-הסיכון והשותפים בהן.

מעלים מצגת עם הפיץ' של הסטארטאפ והוא מוצא לכם את הקרנות הכי רלוונטיות.

[🎗️ Uri Goren @urigoren]

מלחמת ה-AI

[Anthropic @AnthropicAI]

The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees.

The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance.

Access to all other Claude models is not affected.

We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible.

Read our full statement: https://t.co/bwn0sximKZ

[Healthcare AI Guy @HealthcareAIGuy]

NEW: Abridge unveiled an AI-native clinician intelligence platform and announced a collaboration with NVIDIA to build a foundation model for clinical conversations

The platform expands beyond documentation into CDS, workflow automation, coding, payment, & care coordination

[🎗️ Uri Goren @urigoren]

Diffusion Gemma,an interesting shift in text production

[Google @Google]

Meet DiffusionGemma ⚡ Our latest experimental open model (Apache 2.0) that generates text up to 4x faster.

Instead of predicting and typing just one word at a time like most language models, it drafts and refines entire blocks of text simultaneously.

Here’s how it works 🧵 ↓

[🎗️ Uri Goren @urigoren]

@davidasinclair WoW, that is so amazing and exciting

[🎗️ Uri Goren @urigoren]

@Star_Knight12 Sticks & Stones

[🎗️ Uri Goren @urigoren]

@aryanXmahajan OS

[Aryan Mahajan @aryanXmahajan]

Claude + Reddit intelligence + LinkedIn data = Content OS that replaced a $14,500/month team.

(48K followers. 500+ booked calls. $387K in attributed revenue)

This 6-skill system eliminates writers, strategists, researchers, and schedulers using brand memory + real audience intelligence + calibrated AI writers...

→ No more $14,500/month payroll for a 4-person content team
→ No more 20+ hours weekly building content calendars from scratch
→ No more guessing which hooks actually stop the scroll
→ No more AI slop that sounds nothing like you
→ No more starting every post from a blank page

Just 1 topic in → a finished month of content out.

Here's how it works:

→ Brand Memory (your voice, proof, and exact buyer in one file. every skill runs off it. nothing generic ships.)
→ Reddit Intelligence (mines your ICP's subreddits for the exact phrases they use. posts start from real words, not blank pages.)
→ LinkedIn Viral Signal (hooks already stopping the scroll in your niche, last 30 days, ranked by real engagement.)
→ Four Calibrated Writers (thought leadership, lead magnet, story, value. one writer per stage of the buyer journey.)
→ Voice Firewall (7-dimension QA that scores and rewrites every draft before it ships under your name.)
→ Finished Board (every post handed over with its visual and first comment. ready to approve.)

Built on real content infrastructure.
Zero payroll. Consistent output. Enterprise-grade quality.

Results from the system:
- $14,500/month content team eliminated
- 48K LinkedIn followers
- 500+ calls booked from content
- $387K in attributed revenue

Want the complete 6-skill build?

Like + comment "OS" + repost, and I'll DM it to you.
(must be following)

[NextAI4u @NextAI4U]

גוגל הכריזה כעת על שדרוג משמעותי ל-NotebookLM, כלי המחקר הפופולרי שלה המבוסס על AI.

המטרה של העדכון היא להפוך את המערכת מסייע קריאה פסיבי לעוזר מחקר אקטיבי (Agentic), שמסוגל לבצע משימות ניתוח ומחקר מורכבות באופן עצמאי.

היכולות המרכזיות החדשות הן:

1. שילוב מודלי Gemini חדשים ומנוע הסקה מתקדם, שמציגים שיפור של עשרות אחוזים בהבנת מסמכים ארוכים ובמחקר רשת עצמאי.

2. יכולת הרצת קוד (Code Execution) מובנית לצורך ניתוח מדויק של נתונים ומספרים.

3. תמיכה ביצירת קבצים במגוון פורמטים רחב, המאפשרת להנחות את ה-AI להפיק דוחות ותוצרים מותאמים אישית.

4. אפשרות להתחיל פרויקט מחקר מרעיונות כלליים או משאלות בלבד, כשהמערכת משתמשת ב-Google Search כדי למצוא ולהוסיף מקורות מידע רלוונטיים.

5. שמירה על שליטה מלאה של המשתמש, כאשר כל המידע נשאר מבוסס ומגובה במקורות ברורים (Attribution) שניתן לעקוב אחריהם בקלות.

NotebookLM מסוגל כעת לייצר ולהוריד ישירות, מגוון קבצים מעוצבים, לדוגמא:
• דוחות PDF הכוללים טבלאות ותרשימים.
• גיליונות נתונים של Microsoft Excel.
• מצגות מוכנות של Microsoft PowerPoint.
• גרפים דינמיים וויזואליים (כמו קבצי PNG ו-SVG).

אנליסט נתונים יכול להזין מידע ממדינות שונות בפורמטים שונים, לבקש מהכלי לבצע מחקר משלים ברשת, להריץ קוד לניתוח המספרים ולהפיק דוח PDF מעוצב עם גרפים מוכנים להצגה.

העדכונים זמינים כבר עכשיו באופן גלובלי למשתמשי Google AI Ultra וללקוחות עסקיים מסוימים ב-Workspace, ובהמשך יתרחבו למשתמשים נוספים. קרדיט תמונה: Google

בפועל לדעתי, גוגל הופכת את אחד מכלי ה-AI המוצלחים ביותר שלה לסוכן עבודה (Agent) של ממש. היכולת לא רק לסכם חומרים קיימים אלא לחפש באופן יזום ברשת, לכתוב קוד ולפלוט קבצי אופיס מוכנים לעבודה, מסמנת את העתיד שבו ה-AI הופך מעוזר דיגיטלי פשוט לעובד שלוקח פרויקט מקצה לקצה וחוסך שעות של עבודה סיזיפית.

אהבתם? תנו לייק :)
זה עוזר לי מאוד להביא לכם עוד ידיעות עדכניות וחשובות.

[🎗️ Uri Goren @urigoren]

@JakeFleshner Vibe adherence

[Afshine Emrani MD FACC @afshineemrani]

I'm a cardiologist. A 42-year-old mother of two came to my office complaining of jaw pain and crushing fatigue. She ran half-marathons. Her EKG was normal. Another doctor had sent her home with anxiety medication.
When I got her into the cath lab, I found severe microvascular disease — plaque choking the tiniest vessels of her heart, the ones standard angiograms routinely miss.
Her heart had been starving in silence while everyone told her she was stressed.
She is alive today. Too many women like her are not.
Heart disease kills more women than every cancer combined. And medicine is still diagnosing it through a male lens.
84% of cardiologists report having patients in the past year whose heart disease was misdiagnosed by another physician. Women with a STEMI heart attack have a 59% greater chance of being misdiagnosed compared to men. Women with an NSTEMI — 41% greater chance.
The reason is structural. For decades, we screened, tested, and treated women using a template built for men.
Men's heart attacks announce themselves — the crushing chest pain, the clutched fist, the Hollywood collapse. Women's hearts whisper. Crushing fatigue that feels like wearing a lead vest. Jaw pain written off as TMJ. Nausea blamed on a stomach bug. An ache between the shoulder blades blamed on a long week. Shortness of breath blamed on being out of shape.
For years, medicine called these "atypical" symptoms. They are not atypical. They are female-typical. Half of humanity is not a variant.
And the biology runs deeper than symptoms.
Women have smaller hearts and narrower coronary arteries. Plaque doesn't only clog the big highway vessels — it hides in the microvasculature, the tiny branches feeding the heart muscle itself. A woman can have a heart attack with a completely "clean" standard angiogram.
SCAD — spontaneous coronary artery dissection — occurs 90% of the time in women. Often young, fit women with zero traditional risk factors. It's the leading cause of heart attack in women under 50, accounting for roughly one quarter of all cases in that age group. Most doctors have never diagnosed one.
And some of the most dangerous cardiac risk factors are hidden in women's medical histories where no one thinks to look:
Preeclampsia or gestational hypertension doubles to quadruples lifetime heart disease and stroke risk. Pregnancy is the body's first cardiac stress test — and these complications are early warning sirens, not closed chapters.
Autoimmune disease — lupus, rheumatoid arthritis, psoriasis — far more common in women, turbocharges inflammation and plaque formation at any age.
Cardiovascular disease in women aged 20-44 is projected to surge nearly 50% by 2050.
The youngest patients in my practice keep getting younger.
What every woman should ask her doctor — and what every doctor should be asking:
"Given my pregnancy history, autoimmune status, and family history — what is my full cardiovascular risk?" If they don't ask about preeclampsia or gestational diabetes, volunteer it.
"Should I have an Lp(a) test and a coronary calcium score?" Standard cholesterol panels miss too much. Lp(a) is genetic, one-time, and most women have never been tested.
"My tests came back normal but my symptoms haven't stopped — what's next?" Normal stress tests and angiograms can miss microvascular disease, spasm, and SCAD. Persistent symptoms warrant coronary CT angiography or cardiac MRI.
And if something feels wrong — say these exact words to your doctor: "I am concerned this could be my heart."
That single sentence changes the workup. Do not soften it. Do not apologize for it.
80% of heart disease is preventable. But the playbook has to be built for female biology.
Two decades ago, I wrote one of the first books warning that heart disease was the number one killer of women and that medicine was diagnosing it through a male lens. It was recognized by First Lady Laura Bush at the White House during the early years of the national conversation about women's heart health.
I'm haunted by how much of that book I could republish today unchanged.
The science has advanced. The awareness has grown. But the gap between what we know and what happens in the exam room is still costing women their lives.
Share this with every woman you love — and every doctor who treats them. READ MORE: https://t.co/4LRugiY8q2

[🎗️ Uri Goren @urigoren]

My dumb 2 cents , we will have an architecture overhaul for AI because we cant afford not too.

[How To Prompt @HowToPrompt__]

Google has published a paper that might end the transformer era.

For the last 7 years, every major AI, ChatGPT, Claude, Gemini, has been built on the exact same architecture: The Transformer.

But Transformers have a fatal flaw.

To remember context, they have to process every single word against every other word. It’s called quadratic complexity. As your prompt gets longer, the compute cost explodes.

The alternative is the old-school RNN (Recurrent Neural Network). RNNs are incredibly cheap and fast, but they have a fixed memory size. If you give them a long document, they get amnesia.

Until today.

Google researchers published Memory Caching: RNNs with Growing Memory.

And it fixes the biggest bottleneck in AI.

Instead of an RNN having a fixed, rigid memory that constantly overwrites itself, Google gave it a "save" button.

The technique allows the RNN to cache checkpoints of its hidden states as it reads.

The memory capacity of the RNN can now dynamically grow as the sequence gets longer.

They built four different variants, including sparse selective mechanisms where the AI actively chooses exactly which checkpoints matter most.

The results rewrite the rules of efficiency.

On long-context understanding and recall-intensive tasks, these new Memory-Cached RNNs closed the gap with Transformers.

They achieved competitive accuracy without the explosive, quadratic compute cost. It perfectly bridges the gap between the cheap efficiency of an RNN and the massive capability of a Transformer.

We have spent billions scaling Transformers because we thought they were the only way an AI could remember a long conversation.

But Google just proved we don't need to process the whole history every single time.

We just needed a smarter cache.

[🎗️ Uri Goren @urigoren]

@maor_elad @IdoWolf1 @AiSAP_AI דווקא יש אקוסיסטם דיי פורה של מקצוע הרפואה פה:)

[Elad Maor @maor_elad]

לפעמים זה מרגיש לי שהרופא הישראלי היחיד כאן בפלטפורמה הזו הוא @IdoWolf1

בכל מקרה, בימים שני שלישי השבוע הכנס השנתי של האיגוד הישראלי לקרדיולוגיה. מוזמנים לבוא לשמוע אותי בהרצאה שכותרתה
Democratizing AI in Cardiology: From Algorithm to Large
Scale Deployment

@AiSAP_AI

[🎗️ Uri Goren @urigoren]

@urieli17 התשובה: שהדולר יעלה והם ימצו את הסינים 😅