Microsoft Research ✓
@MSFTResearch · joined 21 Feb 2009
We advance science and technology to benefit humanity.
554 917Followers
1 816Following
10 181Posts total
58KViews on collected posts
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A look at how coding agents behave at scale; evaluating AI models that find lymphoma lesions in PET/CT scans; understanding AI chatbot dependence; and advancing large-scale decision-making systems. Dive into the latest issue of Research Focus.: https://t.co/3zSWeoOsh2 https://t.c
9.4K views · 25 likes
· 10 reposts · 4 replies
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2:00
How is AI reshaping the way we work?
Join researchers, builders, and practitioners at The New Future of Work Summit on Sept. 14 for practical workshops, live demos, and research-backed insights on AI and agents.
Free and open to all. Register: https://t.co/7hg3MjUPNe
8.2K views · 19 likes
· 8 reposts · 2 replies
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@MSFTResearch my toxic trait is thinking i could get accepted to this
34 views · 0 likes
· 0 reposts · 0 replies
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Hard truth for my fellow parents: you can helicopter, track their locations, and check their phones, but if a teenager wants to experiment, they’re going to find a way. Just like we did. Just like every generation before us.
We make ourselves sick trying to bubble-wrap our kids.
254 views · 0 likes
· 1 reposts · 1 replies
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Curious about what a future in research could look like? The Microsoft Research Undergrad Internship Program offers hands-on research experience, mentorship, and a chance to explore advanced study. Rising juniors and seniors can apply for 12-week internships in Redmond, NYC, or h
9.9K views · 31 likes
· 15 reposts · 3 replies
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Where can curiosity take a research career?
Undergraduate research intern Matheus Kunzler Maldaner explores agentic systems and finds more than he expected in this first episode of our series, Research | Start Here: Inside the Internship.
See where research can start ▶️ https
9.5K views · 18 likes
· 18 reposts · 2 replies
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1:20
@MSFTResearch Cache-store claims need p99 and p99.9 latency under eviction and checkpoint load. Steady-state throughput can hide pauses that delay an agent service.
4 views · 0 likes
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Honorable Mention: Scalable GPU Acceleration of Scalar Functions in Analytical Databases: Compilation, Benchmarking, and Optimization
Analytical databases support hundreds of scalar functions that often become query bottlenecks. This work introduces a compiler-based approach that
1.8K views · 5 likes
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Best Paper Award: Garnet: A Next-Generation Cache-Store for Accelerating Applications and Services
Garnet reimagines the cache-store layer that powers modern applications and cloud services, helping deliver orders-of-magnitude higher performance and efficiency at scale without ht
2.4K views · 8 likes
· 4 reposts · 3 replies
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We're thrilled to celebrate two Microsoft Research papers recognized at VLDB 2026.
Congratulations to the researchers. https://t.co/URYWHkhIKi https://t.co/nXSyPBfLgO
16.3K views · 40 likes
· 9 reposts · 5 replies
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Rispetto ad account della stessa dimensione
11 post degli ultimi 90 giorni, accanto alla fascia di 100K–1M follower. sotto i pari sia per copertura sia per interazione.
Visualizzazioni mediane2 447questo account6 050mediana per 100K–1M
Copertura, %0.44%questo account1.61%mediana per 100K–1M
Interazione, %0.40%questo account1.01%mediana per 100K–1M
| Metrica | Questo account | Mediana per 100K–1M | Rapporto |
|---|---|---|---|
| Visualizzazioni mediane per post | 2 447 | 6 050 | 0.40× |
| Copertura (visualizzazioni ÷ follower) | 0.44% | 1.61% | 0.27× |
| Tasso di interazione | 0.40% | 1.01% | 0.39× |
Altri account di questa fascia → Confronta con un altro account → Come sono costruiti questi parametri →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
16.3K1 Sep
2.4K
1.8K
42 Sep
9.5K3 Sep
9.9K8 Sep
254
44
34
8.2K9 Sep
9.4K14 Sep
Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.33%1 Sep
0.61%
0.39%
0.00%2 Sep
0.40%3 Sep
0.50%8 Sep
0.79%
2.27%
0.00%
0.35%9 Sep
0.41%14 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.01%.
What the audience does
Likes51.9%147 in total
Reposts23.7%67 in total
Replies7.1%20 in total
Bookmarks17.3%49 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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