Arable helps enterprises achieve ambitious water goals and growers realize high-ROI water stewardship.
Based on the provided content, there is insufficient information to summarize user opinions about Arable. The social mentions consist mainly of YouTube videos titled "Arable AI" without any actual user feedback or review content, plus some unrelated tech news about video search, Whoop fitness devices, and AI reliability. No actual user reviews were provided, and the social mentions don't contain user opinions, complaints, pricing discussions, or meaningful commentary about Arable's performance or reputation. To provide an accurate summary of user sentiment about Arable, I would need access to actual user reviews, detailed social media discussions, or testimonials about the product.
Mentions (30d)
2
Reviews
0
Platforms
3
Sentiment
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0 positive
Based on the provided content, there is insufficient information to summarize user opinions about Arable. The social mentions consist mainly of YouTube videos titled "Arable AI" without any actual user feedback or review content, plus some unrelated tech news about video search, Whoop fitness devices, and AI reliability. No actual user reviews were provided, and the social mentions don't contain user opinions, complaints, pricing discussions, or meaningful commentary about Arable's performance or reputation. To provide an accurate summary of user sentiment about Arable, I would need access to actual user reviews, detailed social media discussions, or testimonials about the product.
Features
Use Cases
Industry
farming
Employees
88
Funding Stage
Series C
Total Funding
$110.0M
Show HN: Gemini can now natively embed video, so I built sub-second video search
Gemini Embedding 2 can project raw video directly into a 768-dimensional vector space alongside text. No transcription, no frame captioning, no intermediate text. A query like "green car cutting me off" is directly comparable to a 30-second video clip at the vector level.<p>I used this to build a CLI that indexes hours of footage into ChromaDB, then searches it with natural language and auto-trims the matching clip. Demo video on the GitHub README. Indexing costs ~$2.50/hr of footage. Still-frame detection skips idle chunks, so security camera / sentry mode footage is much cheaper.
View originalWhoop’s Wearable Fitness Tech Lands $575M From Athletes, Celebrities, Institutional Investors To Reach $10.1B Valuation
Whoop, which provides wearable fitness technology and a subscription platform that tracks physiological data for insights, announced Tuesday that it raised $575 million in Series G funding at a $10.1 billion valuation.
View originalShow HN: Gemini can now natively embed video, so I built sub-second video search
Gemini Embedding 2 can project raw video directly into a 768-dimensional vector space alongside text. No transcription, no frame captioning, no intermediate text. A query like "green car cutting me off" is directly comparable to a 30-second video clip at the vector level.<p>I used this to build a CLI that indexes hours of footage into ChromaDB, then searches it with natural language and auto-trims the matching clip. Demo video on the GitHub README. Indexing costs ~$2.50/hr of footage. Still-frame detection skips idle chunks, so security camera / sentry mode footage is much cheaper.
View originalKarpathy’s March of Nines shows why 90% AI reliability isn’t even close to enough
“When you get a demo and something works 90% of the time, that’s just the first nine.” — Andrej Karpathy The “March of Nines” frames a common production reality: You can reach the first 90% reliability with a strong demo, and each additional nine often requires comparable engineering effort. For enterprise teams, the distance between “usually works” and “operates like dependable software” determines adoption. The compounding math behind the March of Nines “Every single nine is the same amount of work.” — Andrej Karpathy Agentic workflows compound failure. A typical enterprise flow might include: intent parsing, context retrieval, planning, one or more tool calls, validation, formatting, and audit logging. If a workflow has n steps and each step succeeds with probability p, end-to-end success is approximately p^n. In a 10-step workflow, the end-to-end success compounds due to the failures of each step. Correlated outages (auth, rate limits, connectors) will dominate unless you harden shared dependencies. Per-step success (p) 10-step success (p^10) Workflow failure rate At 10 workflows/day What does this mean in practice 90.00% 34.87% 65.13% ~6.5 interruptions/day Prototype territory. Most workflows get interrupted 99.00% 90.44% 9.56% ~1 every 1.0 days Fine for a demo, but interruptions are still frequent in real use. 99.90% 99.00% 1.00% ~1 every 10.0 days Still feels unreliable because misses remain common. 99.99% 99.90% 0.10% ~1 every 3.3 months This is where it starts to feel like dependable enterprise-grade software. Define reliability as measurable SLOs “It makes a lot more sense to spend a bit more time to be more concrete in your prompts.” — Andrej Karpathy Teams achieve higher nines by turning reliability into measurable objectives, then investing in controls that reduce variance. Start with a small set of SLIs that describe both model behavior and the surrounding system: Workflow completion rate (success or explicit escalation). Tool-call success rate within
View originalArable uses a tiered pricing model. Visit their website for current pricing details.
Key features include: TECHNOLOGY, FEATURED USE CASES, Monitor, Optimize, Scale, Enterprises, Quantified Water Savings, Watershed Security.
Arable is commonly used for: TECHNOLOGY.
Based on user reviews and social mentions, the most common pain points are: raised, budget.
Mitchell Hashimoto
Founder at Ghostty / HashiCorp
1 mention
