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Google Research ✓

@GoogleResearch · joined 05 May 2017

Impossible? Let’s see. From algorithms to neuroscience to AI, Google Research strives to progress science, advance society & improve billions of people’s lives.

115 714Followers
17Following
546Posts total
645.3KViews on collected posts

โพสต์ล่าสุด

How do goods travel 450 miles overnight? It’s thanks to careful logistics optimization, particularly in the middle-mile segment, but optimizing these networks is difficult without public data. MilleMiglia provides a standardized benchmark, using spatial clustering and gravity htt
Life of a shipment: from the manufacturer in Groningen (Netherlands) to the customer in Versailles (France), a poffert makes most of its journey in the middle-mile network of the freight forwarder.
7K views · 76 likes · 9 reposts · 7 replies Open on X →
"The best way to predict the future is to invent it." In a deep dive with VP, Google & GM, Google Research @ymatias on The Google Research Podcast, @sineadbovell explored how AI is transforming science & interfaces: 🔹 Ambient AI & GenUI: Interfaces that adapt in real time to ht
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5.5K views · 31 likes · 4 reposts · 6 replies Open on X →
Today we explore the future of practice. We harness generative UI with learning design guardrails to give teachers the ability to generate guided, learning interactive simulations — for every topic & student. Read more + check out the sample library with 30+ STEM interactives ht
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30.6K views · 600 likes · 70 reposts · 17 replies Open on X →
Spanning over 20 years, check out the latest in our AI language research in the 🧵⬇️ 13.1K views · 106 likes · 9 reposts · 3 replies Open on X →
Introducing Retrieve-for-Train: a framework that accelerates complex AI search by replacing heavy autoregressive inference with a lightweight diffusion model. This allows for instant, expert-level search slates at a fraction of the cost. Learn more: https://t.co/cQP0Lmg5kj https:
Overview of the Retrieve-for-Train framework. Step 1: trains a fan-out language model (FOLM) using RL to produce property-aligned sub-queries. Step 2: uses the trained FOLM to synthesize supervision data. Step 3: trains a diffusion-based fan-out retriever that samples content embeddings directly from query embeddings.
86.2K views · 1.5K likes · 153 reposts · 31 replies Open on X →
Google’s work in language research spans over 20 years, beginning in 2006 with Google Translate. Today, these technologies power interactions in over 300 languages, reaching more than 7 billion people—86% of the global population. However, translation and text processing alone h
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15.6K views · 24 likes · 1 reposts · 2 replies Open on X →
@GoogleResearch @HHMIJanelia “Map this, fly!” https://t.co/4odXiR552O 3.3K views · 22 likes · 1 reposts · 0 replies Open on X →
Introducing WeatherNext 3! Built by @GoogleDeepMind and @GoogleResearch, this is our most advanced & accurate AI weather model, and now includes real-time satellite data, hourly refreshes, higher resolution, precise precipitation forecasting, and clean energy variables. Read the 10.2K views · 205 likes · 15 reposts · 9 replies Open on X →
Today on the blog, we evaluate ways to improve cross-population genetic risk prediction. While transfer learning from European cohorts improves prediction in small populations, it degrades accuracy as target cohort sample sizes grow. Learn more: https://t.co/mlL6Ye9kmX https://t. 8.4K views · 108 likes · 6 reposts · 6 replies Open on X →
@GoogleResearch @HHMIJanelia So, in theory, it's possible to create a Sinthetic fly? 3.9K views · 25 likes · 0 reposts · 2 replies Open on X →
@GoogleResearch @HHMIJanelia Can this play doom? 6.9K views · 121 likes · 3 reposts · 3 replies Open on X →
Introducing a complete map of the male fruit fly brain and central nervous system, created in partnership with @HHMIJanelia. With over 166,000 neurons, this is the largest cellular brain map to date. Learn more: https://t.co/nrzbKDdTX1 https://t.co/fW4zL3Uvb8 405K views · 4.9K likes · 495 reposts · 95 replies Open on X →
Methane is a potent greenhouse gas driving approximately 25% of human-induced warming. MAPL-EMIT is a deep-learning model that automates global methane tracking from space to enable scalable climate action. Read the full post and check out the dataset: https://t.co/2y38UXFwno ht 11.9K views · 171 likes · 16 reposts · 10 replies Open on X →
@GoogleResearch Wrote about it here: https://t.co/sbI1D1F8AQ Sadly the terms don't allow us to host it! 13.4K views · 56 likes · 2 reposts · 0 replies Open on X →
@GoogleResearch You guys are miles behind in coding and research and you guys drop this??? 14.4K views · 71 likes · 0 reposts · 10 replies Open on X →
@GoogleResearch oh hell yeah man 9.8K views · 41 likes · 0 reposts · 3 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

16 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 100K–1M ผู้ติดตาม แสดงต่อคนมากกว่าบัญชีขนาดเดียวกัน.

ยอดดูมัธยฐาน11 055บัญชีนี้5 983ค่ามัธยฐานของ 100K–1M
การเข้าถึง, %9.55%บัญชีนี้1.49%ค่ามัธยฐานของ 100K–1M
การมีส่วนร่วม, %1.11%บัญชีนี้0.93%ค่ามัธยฐานของ 100K–1M
ตัวชี้วัดบัญชีนี้ค่ามัธยฐานของ 100K–1Mอัตราส่วน
ยอดดูมัธยฐานต่อโพสต์11 0555 9831.85×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)9.55%1.49%6.41×
อัตราการมีส่วนร่วม1.11%0.93%1.20×

บัญชีอื่นในช่วงนี้ →   เปรียบเทียบกับบัญชีอื่น →   ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

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

13.4K31 Aug
11.9K1 Sep
405K3 Sep
6.9K
3.9K
8.4K
10.2K
3.3K
15.6K15 Sep
86.2K
13.1K
30.6K17 Sep
5.5K18 Sep
7K

Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.43%31 Aug
1.67%1 Sep
1.37%3 Sep
1.84%
0.69%
1.43%
2.25%
0.70%
0.18%15 Sep
1.99%
0.91%
2.25%17 Sep
0.81%18 Sep
1.32%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.93%.

What the audience does

Likes68.5%8 043 in total
Reposts6.7%784 in total
Replies1.7%204 in total
Quotes1.1%134 in total
Bookmarks22.0%2 578 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.

บัญชีที่คล้ายกัน