Query
Find articles
Pick a keyword, optionally a second one to combine it with (and, or, either but not both, or but not), then narrow the articles down by text, source and time range. Keywords update the results right away; filters apply with their button.
Query
How they overlap
Of the articles on each keyword in the last 7 days, with the same text and sources, how many also mention the other. Per lean: the share of its outlets' articles on Amazon that mention artificial intelligence.
19.1% of the 21 articles on Amazon also mention artificial intelligence, as do 0.8% of the 521 articles on artificial intelligence.
- Left-leaning2 of 5 articles
- 40.0%
- Least biased2 of 7 articles
- 28.6%
- Right-leaning0 of 9 articles
- 0.0%
Who picked it up when
CNBC mentioned it first (Oct 22, 2026, 2:07 PM EDT). Least biased outlets followed 2 days later. No right-leaning outlet mentioned it.
One row per source with a matching article, from the most left-leaning on top: a dot for each article, on a bar for each stretch of its coverage (a pause of more than 24 hours starts a new one). Hover or tap a dot for the headline, click it to read the article.
Source lean:leftcenterright
Source leans by Media Bias/Fact Check.
Results
4 articles mention Amazon and artificial intelligence in the last 7 days (Oct 20 to Oct 26).
| Article | |||
|---|---|---|---|
| Forbes | Meta Muse’s 10 Million Users—Why Walmart Wants Them And Amazon Doesn’tForbes As Meta's Muse gains traction, Walmart is betting AI agents will drive new sales. Amazon sees them as a threat to the customer relationships and its commerce ecosystem. | 0.65 | |
| CNBC | Verizon lifts annual forecasts, signs more than $2 billion AI infrastructure deal with AWSCNBC Verizon now expects to add between 1.1 million and 1.2 million postpaid phone subscribers this year compared with earlier projections of 750,000 to 1 million | 0.55 | |
| Hacker News: Front Page | Show HN: Hurston-1 open source TTS that speak Southern American and Afro-EnglishHacker News: Front Page Hey HN, I’m open sourcing my Hurston-1 narrowband TTS model (Apache-2.0). It is very good with American English and does especially well with Southern American and Regional African English accents. Destined AI is based in Atlanta, and I built this because I’m amazed by what AI can do, and I wanted to help introduce and welcome more people to feel comfortable using and interacting with AI. Since 2021, I’ve been collecting fully consented voice data from over 20,000 people, 1M audio recordings, and over 1,800 hrs of audio captured to date. For this model, I used a small part of the data, 136 hrs, to finetune Maya1 and expand it’s capabilities. Hurston-1 is a narrowband TTS model that focuses the output on telephone use because that is still where most of these voices will be heard. I’ve used it to support customers such as Amazon and Salesforce and generated over half-mill revenue with it. Now I’m open sourcing it to help unlock opportunities for others as well. Limitations: this model doesn’t maintain the exact same voice across prompts and doesn’t support voice cloning. For many use cases, this is fine but maybe not so - if you’re creating podcasts. This is the first release - I’m already working on the next version with improvements. I would appreciate, if anyone is interested in this space, download the model from huggingface, check it out and let me know any feedback. Also, open to connecting with others in this space as well. Comments URL: https://news.ycombinator.com/item?id=50227330 Points: 54 # Comments: 23 | 0.40 | |
| CNBC | Personal agents like Meta's Muse could fuel AI’s growth — and challenge Amazon and AppleCNBC Meta's Muse is taking off, but analysts say it's only the beginning | 0.65 |
Source leans by Media Bias/Fact Check.
Narrow further
Other keywords in the matching articles: the share of them that mention each, with the number of articles. The search icon searches for Amazon and that keyword instead of artificial intelligence, keeping the text, sources, source type and time range.
Coverage by source
The share of each source's stories in the last 7 days that match the query, from left to right. Sort the table to reorder the bars.
Source lean:leftcenterright
Source leans by Media Bias/Fact Check.
| CNBC | 0.6% | 2 | 328 |
| Hacker News: Front Page | 0.6% | 1 | 164 |
| Forbes | 0.3% | 1 | 408 |
Coverage by lean
The share of stories that match the query, in the last 7 days, averaged over the outlets of each political lean with at least 3 stories. The groups differ in size, so a single outlet weighs more in the smaller ones.
- Left-leaning1 of 15 sources
- <0.1%
- Least biased2 of 8 sources
- 0.1%
- Right-leaning0 of 15 sources
- 0.0%
Lean index −1.4: covered more by left-leaning outlets
Each outlet at its MBFC bias score, from −10 (far left) to +10 (far right), as high as the share of its stories that match the query. The lean index is the average score of the outlets covering it, weighted by that share.
lean indexour sources' average (+0.4)leftcenterright
Bias scores by Media Bias/Fact Check.
Source leans based on ratings by Media Bias/Fact Check.