Amazon Science ✓

@AmazonScience · Global · joined 10 Dec 2019

The latest news and research from Amazon's science community. #AmazonScience

92 103Followers

1 917Following

7 626Posts total

97KViews on collected posts

Postingan terbaru

Amazon Science ✓@AmazonScience4 Sep

.@Amazon and @DARPA brought together 150+ researchers in Seattle last week, with speakers including @awscloud CEO @mattsgarman, Fields Medalist @TaoistTerence, @EPrinceton Associate Professor @BorisHanin, and @NSAGov's Michael O'Hara to explore how AI is transforming mathematical

10.8K views · 22 likes · 3 reposts · 2 replies Open on X →

Amazon Science ✓@AmazonScience2 Sep

Amazon Redshift researchers were awarded Best Paper Runner-Up: Industrial Track at @VLDBconf for eliminating compilation cold starts in query execution – cutting compilation time from seconds to milliseconds with a 7x speedup on TPC-DS benchmarks. #VLDB2026 2.4K views · 12 likes · 0 reposts · 0 replies Open on X →

Amazon Science ✓@AmazonScience1 Sep

@AmazonScience @blackenedgold @InferenceLang provides native compilation to WebAssembly with auto formalization to @CoqLang out of the box. Currently, proof holes auto completion is in closed beta but will be available soon 276 views · 1 likes · 0 reposts · 0 replies Open on X →

Amazon Science ✓@AmazonScience31 Aug

@AmazonScience spec is still a trap 2.7K views · 4 likes · 0 reposts · 0 replies Open on X →

Amazon Science ✓@AmazonScience31 Aug

@AmazonScience the proof only says the code matches the spec, so the whole thing rests on the spec being what you actually wanted. it pays off where the spec is way shorter than the code, which is what isolation primitives are. gets a lot worse the further up you go 2.2K views · 5 likes · 0 reposts · 0 replies Open on X →

Amazon Science ✓@AmazonScience31 Aug

Verus is an open-source, automated program verifier for Rust that mechanically checks code against a formal mathematical specification for all possible inputs. Amazon used it to prove correctness of Nitro Isolation Engine primitives. https://t.co/SuFeU5g8nf 73.9K views · 541 likes · 70 reposts · 8 replies Open on X →

Amazon Science ✓@AmazonScience28 Aug

When LLM judges agree, the right question is why. Shared prompts, model families, or training lineage can make a majority look stronger than it is. Dependence-aware aggregation via Ising models accounts for this, improving accuracy 9–14% over weighted majority vote. 2.9K views · 14 likes · 5 reposts · 0 replies Open on X →

Amazon Science ✓@AmazonScience25 Aug

How did a model upgrade make agents worse? By pairing real enterprise SOPs with functioning tools and ground-truth grading across 12 industries and 2,000+ tasks, SOP-Bench helps find such anomalies. https://t.co/B2NarMII2B 1.7K views · 2 likes · 0 reposts · 0 replies Open on X →

Dibandingkan akun berukuran sama

8 postingan dari 90 hari terakhir, dibandingkan dengan rentang 10K–100K pengikut. jangkauan biasa untuk ukurannya, reaksi lebih lemah dari kebanyakan.

Median tayangan2 582akun ini982median untuk 10K–100K

Jangkauan, %2.80%akun ini3.62%median untuk 10K–100K

Interaksi, %0.32%akun ini1.94%median untuk 10K–100K

Metrik	Akun ini	Median untuk 10K–100K	Rasio
Median tayangan per postingan	2 582	982	2.63×
Jangkauan (tayangan ÷ pengikut)	2.80%	3.62%	0.77×
Tingkat interaksi	0.32%	1.94%	0.16×

Akun lain pada rentang ini → Bandingkan dengan akun lain → Bagaimana tolok ukur ini disusun →

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

1.7K25 Aug

2.9K28 Aug

73.9K31 Aug

2.2K

2.7K

2761 Sep

2.4K2 Sep

10.8K4 Sep

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.11%25 Aug

0.66%28 Aug

0.86%31 Aug

0.23%

0.15%

0.36%1 Sep

0.50%2 Sep

0.28%4 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.94%.

What the audience does

Likes52.7%601 in total

Reposts6.8%78 in total

Replies0.9%10 in total

Quotes1.5%17 in total

Bookmarks38.1%434 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.

Postingan terbaru

Dibandingkan akun berukuran sama

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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