Technology

As government regulation for commercial drone usage seems to be trending in a very positive direction for the companies involved, there is an ever-growing opportunity for drone startups to utilize artificial intelligence to deliver insights without requiring much human effort.

Sterblue, a French drone software startup that is launching out of Y Combinatorlatest class of companies, is aiming to get off-the-shelf drones inspecting large outdoor structures up close with automated insights that identify anomalies that need a second look.

The startupsoftware is specifically focused on enabling drones to easily inspect large power lines or wind turbines with simple automated trajectories that can get a job done much quicker and with less room for human error. The software also allows the drones to get much closer to the large structures they are scanning so the scanned images are as high-quality as possible.

Compared to navigating a tight urban environment, Sterblue has the benefit of there being very few airborne anomalies around these structures, so autonomously flying along certain flight paths is as easy as having a CAD structure available and enough wiggle room to correct for things like wind condition.

Operators basically just have to connect their drones to the Sterblue cloud platform where they can upload photos and view 3D models of the structures they have scanned while letting the startupneural net identify any issues that need further attention.All and all, Sterblue says their software can let drones get within three meters of power lines and wind turbines, which allows their AI systems to easily detect anomalies from the photos being taken. Sterblue says their system can detect defects as small as one millimeter in size.

The startup was initially working on their own custom drone hardware but decided that their efforts were best spent supporting off-the-shelf devices from companies like DJI, with their software solution sitting on top.The founding team is composed of former Airbus employees that are focusing early efforts on utility companies, with some of the first customers based in Europe, Africa and Asia.

Cryptocurrency projects can crash and burn if developers don&t predict how humans will abuse their blockchains. Once a decentralized digital economy is released into the wild and the coins start to fly, ittough to implement fixes to the smart contracts that govern them. Thatwhy Incentivai is coming out of stealth today with its artificial intelligence simulations that test not just for security holes, but for how greedy or illogical humans can crater a blockchain community. Crypto developers can use Incentivaiservice to fix their systems before they go live.

&There are many ways to check the code of a smart contract, but thereno way to make sure the economy you&ve created works as expected,& says Incentivaisolo founder PiotrGrudzień. &Icame up with the idea to build a simulation with machine learning agents that behave like humans so you can look into the future and see what your system is likely to behave like.&

Incentivai will graduate from Y Combinator next week and already has a few customers. They can either pay Incentivai to audit their project and produce a report, or they can host the AI simulation tool like a software-as-a-service. The first deployments of blockchains itchecked will go out in a few months, and the startup has released some case studies to prove its worth.

&People do theoretical work or logic to prove that under certain conditions, this is the optimal strategy for the user. But users are not rational. Therelots of unpredictable behavior thatdifficult to model,&Grudzień explains. Incentivai explores those illogical trading strategies so developers don&t have to tear out their hair trying to imagine them.

Protecting crypto from the human x-factor

Thereno rewind button in the blockchain world. The immutable and irreversible qualities of this decentralized technology prevent inventors from meddling with it once in use, for better or worse. If developers don&t foresee how users could make false claims and bribe others to approve them, or take other actions to screw over the system, they might not be able to thwart the attack. But given the right open-ended incentives (hence the startupname), AI agents will try everything they can to earn the most money, exposing the conceptual flaws in the projectarchitecture.

&The strategy is the same as what DeepMind does with AlphaGo, testing different strategies,&Grudzień explains. He developed his AI chops earning a masters at Cambridge before working on natural language processing research for Microsoft.

Herehow Incentivai works. First a developer writes the smart contracts they want to test for a product like selling insurance on the blockchain. Incentivai tells its AI agents what to optimize for and lays out all the possible actions they could take. The agents can have different identities, like a hacker trying to grab as much money as they can, a faker filing false claims or a speculator that cares about maximizing coin price while ignoring its functionality.

Incentivai then tweaks these agents to make them more or less risk averse, or care more or less about whether they disrupt the blockchain system in its totality. The startup monitors the agents and pulls out insights about how to change the system.

For example, Incentivai might learn that uneven token distribution leads to pump and dump schemes, so the developer should more evenly divide tokens and give fewer to early users. Or it might find that an insurance product where users vote on what claims should be approved needs to increase its bond price that voters pay for verifying a false claim so that itnot profitable for voters to take bribes from fraudsters.

Grudzień has done some predictions about his own startup too. He thinks that if the use of decentralized apps rises, there will be a lot of startups trying to copy his approach to security services. He says there are already some doing token engineering audits, incentive design and consultancy, but he hasn&t seen anyone else with a functional simulation product thatproduced case studies.&As the industry matures,I think we&ll see more and more complex economic systems that need this.&

As limited partners increasingly demand greater exposure to emerging market opportunities, venture capital firms with a focus on Asia are bulking up their funds and chasing deals in an increasingly competitive race to own stakes in the next generation of local startups with global aspirations.

Over the last year, firms, including DCM Ventures, GGV Capital,Matrix Partners China and Qiming Venture Partners, have all significantly increased the targets for their new funds. If each firm hits their targets, thereroughly $4.4 billion in new capital that could be flooding into an already scorching market for investment into Chinese startups, according to SEC filings.

The largest of these new funds, by far, is GGV Capital, which has registered a new $1.8 billion fund with the Securities and Exchange Commission. Qiming Ventures has targeted $900 million for its latest fund, while DCM Ventures and Matrix Partners China are each looking for $750 million for their own new investment vehicles, according to securities filings.

Managing partners at the firms did not respond to a request for comment.

These four firms are among the last standing from the initial flood of U.S.-based venture capital firms that poured into Asia (and China specifically) in the first decade of the new millennium.

While marquee names like Kleiner Perkins, DFJ and others foundered in China, these four firms (along with global venture capital juggernauts like Sequoia Capital and NEA) put down deep roots and notched notable wins with investments in startups like Didi Chuxing, Kuaidi, Meituan-Dianping, Xiaomi and many more.

In part, these massive new funds are simply a response to the new world that venture investors find themselves in thanks to the massive amounts of capital raised by SoftBank with its $100 billion Vision Fund, or Sequoia with its $9 billion new investment vehicle.

Firms are also under pressure to raise more capital from limited partners, who want to reduce their exposure and consolidate their own investments around venture firms with track records of success and the ability to deploy capital into larger checks.

Couple those facts with the (still) low cost of capital given where interest rates are, and the sustained growth of technology companies across emerging market geographies, and you have a more willing pool of investors that want to commit more capital to emerging technology ecosystems (this is happening in Latin America, too).

But there are also some contours of Chinacompetitive environment that are pushing these venture capital firms to raise increasingly larger funds.

One is the sheer size of the opportunity that exists for new technology companies in China. As the WeChat messaging service increasingly evolves into a new operating system, there are opportunities to scale quickly with larger infusions of capital to capture the market.

Like their peers in the U.S., Chinese companies are also delaying their public offerings and spending more time to build a better outcome with their IPOs. Thatputting pressure on earlier-stage investors to raise capital so they don&t get crowded out in those later-stage rounds.

Chinese entrepreneurs are also often putting in their own money to finance companies at the earliest stages, which means startups are more mature when they&re seeking their first round. Itthis phenomenon that leads to the $100 million Series A and B rounds that crop up in the Chinese market more regularly than in the U.S.