An HBR research listed three main reasons underlying these astonishing results: the early role of military R&D and the mandatory military service role in building entrepreneurial culture, good relations with the U.S. and the fact that early success breeds continued success.

The average funding round is $12.15 million according to the 2015 Annual Report on Startup and Venture Capital in Israel (only considering rounds above above $500,000) and foreign investors, China in particular, play an important role.

We decided to analyse this fascinating market and to highlight 10 startups that are growing under the radar. We believe they deserve to be discovered, and who knows, maybe one day they will become the champions of the world economy!

Why these companies?
These companies displayed exceptional performance on important success factors – strength of the team, size of the opportunity, competitive environment, etc. – while not being on the radar of investors and media websites.

Most competitions are biased towards companies that reached the largest number of milestones. We tried to avoid this bias, and reward companies on abnormal performance no matter their development stage.

The List
So here it is, the top 10 undiscovered startups from Israel:

1| Bwareit
BwareIT is an Israeli Startup that develops BrighTap water meter module and WADP- Water quality and consumption Analytic Data Platform (includes app and web services). BrighTap IOT water meter is standalone device attached to any standard water tap, pipe or hose and transforms them to a Smart device. In additional BrighTap module can be OEM to any device (Tab, Refrigerator, water Bar). BwareIT combines unique and in-house developed analytic algorithm and turbine technology that measures water flow, with accuracy +/- 4%.
brightap.com

2| VRPhysio
VRPhysio is making smart virtual reality devices for physiotherapy and preventive workout. VRPhysio aims to change the world of physiotherapy by turning home physiotherapy workout fun, easy with real time monitoring and biofeedback, accessible to both the user and the physiotherapist.

vrphysio.com

3| Apeo
Apeo allows you to create in seconds stylish looking polls from any device and share through any of your ongoing chats and social channels. The poll results are displayed in the app in real time. We sought out to introduce community wisdom to everyday life. Apeo lets you reach out to your wide audience or consult your inner circle – you’re in control. The answers are anonymous so you know you’re getting them right.

apeo.co

4| Fifth Dimension
Fifth Dimension fuses massive amounts of data, from any collection source, of any type and any format, and applies deep learning artificial intelligence to provide an accurate, holistic, automated intelligence. Applications include both security and defence and enterprise solutions.

5dimension.com

5| hoop
hoop is an iOS app and a video playground where people can connect and collaborate through “social video chains” — horizontal threads of short videos by various participants that are sorted by popularity. Chains evolve dynamically and can host video trends, challenges, collaborations and more.
hoop.mobi

6| Zeek
Zeek is on a mission to rescue $100 billion worth of unused gift cards and vouchers for users. Zeek is a web-based and app marketplace platform that allows users to buy gift vouchers for over 350 leading UK brands at discounted rates as well as sell their unwanted gift vouchers quickly and easily.

zeek.me

7| mmuze
With mmuze, messaging becomes the leading online shopping channel. mmuze personal shopping assistant bot-as-a service automatically connects to your catalog, chats with your customers, understands their needs, and leverage popular features and social trends intelligence to offer your best-fit products.

mmuze.com

8| Howazit
Howazit is a smart, simple, end­-to-­end customer communication platform. Comprised of a suite of products that make sure businesses are delivering on their brand promise, Howazit offers chat-­based collection of feedback, automated chat-­like support with the opportunity for up-selling, and advanced trigger-­based marketing engines.

howazit.com

9| Spaceek
Spaceek is a data driven company developing a complete system for navigating drivers efficiently to a parking spots and managing indoor and outdoor parking based on real-time data. We believe that considering the parking challenge, good decisions can only be taken based on accurate data and with a wide system approach.

spaceek.com

10| FunTasKid
ADHD children experience much difficulties in learning their daily tasks.
Get them dressed, clean their room, brush their teeth by themselves is an endless frustrating and challenging parent burden. That’s where Funtaskid mobile app comes in and transforms the boring daily routines into a fun game. Let them be independent getting them doing it on their own!
funtaskid.com

About Equidam
Equidam is the leading online valuation platform worldwide. More than 15.000 companies in 78 countries use Equidam to calculate, display and negotiate their valuation. Its algorithm combines the most used 5 valuation methods and benchmarks information with aggregated data across several industries to provide accurate valuations at 1/10 the time of a standard valuation service.

Original post: https://www.equidam.com/top-israeli-startups-july-2016/

VR video can be categorized as 3DOF (three degrees of freedom) or 6DOF (six degrees of freedom). 3DOF responds only to rotation, while 6DOF responds to both rotation and translation—meaning you get to move your head. VR games are 6DOF, but most VR videos are 3DOF. 3DOF can cause motion sickness and eye strain due to incorrect 3D rendering. 6DOF VR video fixes these problems for a more comfortable and immersive experience, but it is harder to make because it requires a 3D model of each frame of video.

There are some prototypes for 6DOF VR video systems in big tech, but they typically involve arrays of many cameras, so they are expensive, not very portable, and generate an impractical amount of data. Because of these challenges, 6DOF hasn't been widely adopted by VR video creators.

In 2015 I was working on ads at Facebook, but I was more excited about VR. I built 3D cameras out of legos and GoPros, showed some of this at a hackathon, and eventually they let me do that as my day job. I was the first engineer on Facebook's 3D VR camera team, which made Surround 360 (an open-source hardware/software 3D VR camera), and Manifold (a ball of 20+ cameras for 6DOF). After Facebook, I was a tech lead on Lyft's self-driving car project, and Google X's everyday robot project.

I started Lifecast because I wasn't satisfied with the progress on 6DOF VR video since I left Facebook. I learned new ideas from robotics which can improve VR video. The Oculus Quest 2 has just enough power to do something interesting with 6DOF. There have also been advances in computer vision and deep learning in the last few years that make it possible to do 6DOF better.

Our software makes it simple to create 6DOF VR video using any VR180 camera. It's a GUI for Mac or Windows, which takes VR180 video or photos as input, and produces Lifecast's 6DOF VR video format (more info: https://fbriggs.medium.com/6dof-vr-video-from-vr180-cameras-...). VR180 video can be created with any VR180 camera; the Canon R5 is one of the best on the market right now. We make a video player for WebVR which runs on desktop, mobile or VR. Playing the videos on the Quest 2 doesn't require installing any software, just visiting a web page in the Oculus Browser.

In addition to our 6DOF format, the software can also output point clouds (.pcd) or triangle meshes (.obj) compatible with Unreal Engine. We are seeing interest in using this for virtual production (2D film-making in a game engine), and creating environments for robotics simulation.

This recent video review/tutorial does a nice job of explaining our tech: https://www.youtube.com/watch?v=_4a-RnTLu-I (video by Hugh Hou, not us). For something more interactive, the thumbnails on https://lifecastvr.com are links to demos that run in browser/VR.

6DOF VR video is one piece of a larger puzzle. We envision a future where people wear AR glasses with 3D cameras, and use them to record and live-stream their experience. 3DOF is not sufficient for this because it causes motion sickness if the camera moves. We have prototypes which fix motion sickness in 3D POV VR video from wearable cameras. Watching the videos in VR feels like reliving a memory. Here's a demo: https://lifecastvr.com/trickshot.html

You can download a free trial from https://lifecastvr.com after entering your email address, but do not need to create a full account. The free trial is not limited in any way other than putting a watermark on the output.

We’d love to hear your thoughts and experiences about VR video, virtual production and robotics!

Kevin and I met while working at Roblox. We talked to our friends who were junior developers and noticed a lot of them doing grunt work. We wanted to let them focus on important work. Copilot is great, but we realized some tasks could be completely offloaded to an AI (e.g. adding a banner to your webpage https://github.com/sweepai/landing-page/issues/225).

Sweep does this with a code search engine. We use code chunking, ranking, and formatting tricks to represent your codebase in a token-efficient manner for LLMs. You might have seen our blog on code chunking here: https://news.ycombinator.com/item?id=36948403.

We take these fetched code snippets and come up with a plan to write the PR. We found that having the LLM provide structured information using XML tags is very robust, as it’s easy for us to parse with regex, has good support for multi-line answers and is hard for the LLM to mess up.

This is because XML is common in the LLM’s training data (the internet / HTML), and the opening and closing tags rarely appear naturally in text and code, unlike the quotations, brackets, backticks and newlines used by JSON’s and markdown’s delimiters. Further, XML lets you skip the preamble (“This question has to do with xyz. Here is my answer:”) and handles multi-line answers like PR plans and code really well. For example, we ask the LLM for the new code in <new_code> tags and a final boolean answer by writing <answer>True</answer>.

We use this XML format to get the LLM to create a plan, generating a list of files to create and modify from the retrieved relevant files. We iterate through the file changes and edit/create the necessary files. Finally, we push the commits to GitHub and create the PR.

We’ve been using Sweep to handle small issues in Sweep’s own repo (it recently passed 100 commits). We’ve become well acquainted with its limitations. For example, Sweep sometimes leave unimplemented functions with just “# rest of code” since it runs on GPT-4, a model tuned for chatting. Other times, there’s minor syntax errors or undefined variables. This is why we spend the other half of our time building self-recovery methods for Sweep to fix and test its PRs.

First, we invite the developer to review and add comments to Sweep’s pull request. This helps to a point, but Sweep’s code sometimes wouldn’t lint. This is table stakes. It’s frustrating to have to tell the bot to “add an import here” or “this variable is undefined”.
To make this better, we used GitHub Actions, which automatically runs the flow of “check the code → tell sweep → sweep fixes the code → check the code again”. We like this flow because you might already have GitHub Actions, and it’s fully configurable. Check out this blog to learn more https://docs.sweep.dev/blogs/giving-dev-tools.

So far, Sweep isn’t that fast, can’t handle massive problems yet, and doesn’t write hundreds of lines of code. We’re excited to work towards that. In the meantime, a lot of our users have been able to get useful results. For example, a user reported that an app was not working correctly on Windows, and Sweep wrote the PR at https://github.com/sweepai/sweep/pull/368/files, replacing all occurrences of "/tmp" with "tempfile.gettempdir()". Other examples include adding a validation function for Github branch name (https://github.com/sweepai/sweep/pull/461) and adding dynamically generated initials in the testimonials on our landing page (https://github.com/wwzeng1/landing-page/issues/28). For more examples, checkout https://docs.sweep.dev/examples.

Our focus is on finding ways that an AI dev can actually help and not just be a novelty. I think of my daily capacity to write good code as a stamina bar. There’s a fixed cost to opening an IDE, finding the right lines of code, and making changes. If you’re working on a big feature and have to context switch, the cost is higher. I’ve been leaving the small changes to Sweep, and my stamina bar stays full for longer.

Our repo is at https://github.com/sweepai/sweep, there’s a demo video at https://www.youtube.com/watch?v=WBVna_ow8vo, and you can install Sweep here: https://github.com/apps/sweep-ai. We currently have a freemium model, with 5 GPT-4 PRs at the free tier, 120 GPT-4 PRs at the paid tier and unlimited at the enterprise tier.

We’re far from our vision of a full AI software engineer, but we’re excited to work on it with the community feedback :). Looking forward to hearing any of your thoughts!