May 22, 2024

Krazee Geek

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These AI startups had been among the many frontrunners in Y Combinator’s Winter 2024 batch

5 min read

Despite an general decline in startup funding, funding for AI has elevated prior to now yr. Capital for generative AI ventures alone is projected to say no roughly from 2022 to 2023, reaching $25.2 billion by the top of December.

So it is by no means shocking that Y Combinator’s Winter 2024 Demo Day was dominated by AI startups.

According to YC’s official startup listing, there are 86 AI startups within the Y Combinator Winter 2024 cohort – virtually double the quantity from the Winter 2023 batch and near triple the quantity from Winter 2021. Call it bubble or hyperbole, however clearly, AI is the expertise of the second.

as we did Last yr, we went by means of the most recent Y Combinator group — the group presenting throughout this week’s Demo Day — and picked out among the extra attention-grabbing AI startups. Each made the minimize for various causes. But at a elementary degree, they stood out from the remainder, whether or not for his or her expertise, addressable market or the background of the founders.


August Chen (ex-palantir) and Alton Losner (ex-Boston Consulting Group) declare that the federal government contracting course of is hopelessly damaged.

Contracts are posted on 1000’s of various web sites and might comprise tons of of pages of overlapping guidelines. (The US federal authorities alone indicators estimated Over 11 million contracts per yr.) Responding to those bids can take the equal of total enterprise divisions supported by exterior consultants and legislation companies.

Chen & Losner’s resolution to automating the federal government contract search, drafting, and compliance course of is AI. The pair – who met in school – name it Walnut,


Image Credit: Walnut

Using Hazel, customers can match potential contracts, generate a draft response primarily based on the RFP and their firm info, create a guidelines of duties, and routinely run compliance checks.

Looking on the development of AI to mislead, I’ve little doubt that Hazel’s generated responses and checks shall be persistently correct. But, even when they had been shut, they might save huge quantities of effort and time, giving smaller corporations an opportunity on the tons of of billions of {dollars} price of presidency contracts issued every year.

andy ai

Home nurses deal with loads of paperwork. Tiantian Zha is aware of this effectively – she beforehand labored at Google’s guardian firm Verily Alphabetthe place she was concerned in efforts starting from customized drugs to lowering mosquito-borne illnesses.

During her work, Jha found that documentation was an enormous time-waster for dwelling nurses. According to at least one this can be a widespread challenge StudyNurses spend greater than a 3rd of their time on documentation, slicing into time spent on affected person care contribute to burnout,

To assist ease the documentation burden for nurses, Jha co-founded andy ai With ex Max Akhmatov Apple Pari-Engineer. Andy is principally an AI-powered scribe that captures and transcribes spoken notes throughout affected person visits and creates digital well being information.

andy ai

Image Credit: andy ai

Like any AI-powered transcription instrument, there may be additionally hazard of bias – that means the instrument will not be working effectively for some nurses and sufferers primarily based on their pronunciation and selection of phrases and, from a aggressive perspective, Andy will not be the primary product of its variety in the marketplace – opponents embrace deepscribe, heidi well being, Nabla And Amazon’s AWS HealthScribe,

however as healthcare quick After the shift to dwelling, the demand for apps like Andy AI is more likely to enhance.


If your expertise with climate apps is like this reporter’s, you have been caught in a storm after blindly believing predictions of clear blue skies.

But it does not need to be this fashion.

At least, that is the premise of AI-powered climate forecasting platform Precip. Jesse Vollmer got here up with the concept after founding FarmLogs, a startup that sells crop administration software program. He teamed up with Sam Pierce Lola and Michael Asher, beforehand chief information scientists at FarmLogs. especially A actuality.


Image Credit: particularly

Precip offers evaluation on precipitation, for instance estimating the quantity of precipitation over a given geographic space over the previous a number of hours to days. Vollmer claims Precip can generate “high-precision” metrics for any location within the US all the way down to a kilometer (or two), forecasting circumstances as much as seven days forward.

So what is the worth of rainfall metrics and alerts? Well, Vollmer says farmers can use them to trace crop development, development crews can refer them to schedule crews and utilities can use them to anticipate service disruptions. Vollmer claims {that a} transportation buyer checks the precip each day to keep away from dangerous driving circumstances.

Of course, there isn’t any scarcity of climate forecast apps. But AI likes precip’s guarantees Make Forecast More Pure – If AI is actually price it.


Claire Wiley launched a {couples} teaching programming whereas finding out for her MBA at Wharton. The expertise led him to research a extra tech-forward strategy to relationships and remedy, culminating in Maya,

Maia – which Wiley co-founded with former Google Research scientist Ralph Ma – goals to empower {couples} to construct stronger relationships by means of AI-powered steering. In Maia’s apps for Android and iOS, {couples} message one another in group chats and reply each day questions like what challenges they need to overcome, previous ache factors and a listing of issues they’re eager for. Is grateful.


Image Credit: Maya

Maia plans to become profitable by charging for physician-crafted packages and premium options like limitless messaging. (Maya usually limits texts between companions – a frustratingly arbitrary restrict in the event you ask me, however that is simply the best way it’s.)

Willie and Ma, each of whom come from divorced properties, say they labored with a relationship professional to craft the Maia expertise. However, I’ve questions, (1) how good is Maia’s relationship science and (2) can it stand out within the exceptionally crowded area of {couples} apps? We must wait and see.


The AI ​​fashions on the coronary heart of generative AI apps like ChatGPT are educated on large information units, a mixture of public and proprietary information from across the internet, together with ebooks, social media posts, and private blogs. But a few of this information is legally and ethically problematic – to not point out flawed Other Ways,

If you ask Serena Ge and Charlie Lee, the issue is the obvious lack of information curation.

Ge and Li co-founded datacurve, which offers “expert-quality” information for coaching generative AI fashions. This is especially coded information, which Ge and Li say is especially tough to acquire due to the experience required to label it for AI coaching and restrictive use licenses.


Image Credit: datacurve

DataCurve hosts a gamified annotation platform that pays engineers to resolve coding challenges, contributing to DataCurve’s for-sale coaching information units. Ge and Li say these information units can be utilized to coach fashions for code optimization, code technology, debugging, UI design, and extra.

This is unquestionably an attention-grabbing concept. But Datacurve’s success will rely upon how effectively curated its information units are – and whether or not it is ready to incentivize sufficient builders to proceed constructing and bettering them.

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