Really excited to bring hedge fund level economic modeling and portfolio analysis to everyone. Our incredible but small team built PortfolioPilot and has spent a lot of time over the last few weeks ironing out issues with the plugin. You can try it out in ChatGPT today and please give us your feedback - that's the only way for us to improve it!
What was the submission process like? You're a small startup so I'm curious to learn about what Open AI saw in your team to put you in the early batch of plugins
I think having this plugin be a natural extension of an existing product was very useful, as well as the large interest in our project once we announced it publicly
We can launch the engine into VPC we manage that is co-located in your region/AZ, and peer the networks, instead of offering a traditional multi-tenant hosted solution.
But we try _really_ hard to ensure your data is never exposed to the Internet. And we do everything we can to limit our ability to read your data, either through self-hosting or ensuring you own the keys.
The Iris Automation system can see much further and track dynamic objects like aircraft, balloons, birds, etc. This article does a pretty good job of summing up why we need much more than the "bumper solutions" you mention above: https://medium.com/@alexharm/why-situational-awareness-is-ab...
How do they handle tracking dynamic objects if they are also moving dynamically? Is it just a SLAM method, where you can identify objects between frames?
The only way I have seen this done us using post-processing on object edges. There is no horizon, so it would be pretty difficult to do in real time (I.e. ~20 fps), perhaps to slow to make decisions.
The system is much more than just a basic SLAM algorithm, allowing it to have a full picture of the world, tracking both static and dynamic obstacles that the drone may encounter.
The technologies in the OP are also attempting to provide a solution for air traffic collision avoidance. What is the specific use case Iris will solve better than any other existing technology?
What is the business case for drone delivery with regard to energy efficiency and total cost of ownership and fundamentally to deliver? Except for high value, low-weight items, how do you see competition in the coming years in the face of fleets of autonomous terrestrial vehicles that don't have to lift their payloads into the air?
I know Amazon has said previously most of their items "can" be delivered by drone, but the question remains should and will they, considering the high cost of current battery technology. Will it ever really be financially viable to lift items into the air in an individual manner when you can get them to their destination far more efficiently via the ground? It seems to me the case is for elimination of the human component in delivery.
If drone delivery is really so important, why aren't the major shipping companies working on it and scraping their existing air freight and hub and spoke distribution systems?
The article makes it sound like this is primarily for the drone delivery segment. That makes some sense, because it's at least easy to define the end goal. Do you also have plans for applications where the goal isn't as easy to define? That is, what can you automate beyond obstacle detection/avoidance?
Sounds like the package delivery part was more for journalistic flair than the core market. Collision avoidance beyond-line-of-sight is useful for pipeline inspection, agricultural surveys, search & rescue, forestry management, and many more use cases!
Alex, what is the maximum detection distance you expect is required for Iris to successfully negotiate an avoidance maneuver in its concept of operation. Further, what are the typical targets/obstacles that Iris would intend to detect and avoid?
Seems this didn't get any love, so I'll clarify. There is a tradeoff in exposure area and distance, for a given data rate out of the sensor. Because there are already many projects related to obstacle avoidance in the near field, I am curious if Iris chooses to address traditional air traffic targets (as depicted on the website image). If this is the case, what types of aircraft and at what distances. Put yet another way, does Iris intend to compliment traditional TCAS-like systems (albeit for non-cooperative targets)?
One of the major advantages of the Iris system is being able to deal with other aircraft in the national airspace (especially non-cooperative targets like you mention). It means that any system that will actually be useful will have to be able to see and track objects correctly further than 500m away, like Iris can.
> Today’s SLAM systems help machines geometrically understand the immediate world (i.e., build associations in a local coordinate system) while today’s Deep Learning systems help machines reason categorically (i.e., build associations across distinct object instances). In conclusion, I share Newcombe and Davison excitement in Visual SLAM, as vision-based algorithms are going to turn Augmented and Virtual Reality into billion dollar markets. However, we should not forget to keep our eyes on the "trillion-dollar" market, the one that's going to redefine what it means to "work" -- namely Robotics. The day of Robot SLAM will come soon.
I know it's very early for you guys, but I was curious if you have a ballpark for your product price? Even cheap LIDARs still cost a decent penny, and camera only systems have issues with drift.
One of the main reasons we choose to go with simple cameras is because it can be so much cheaper than LIDAR and RADAR sensors. Won't disclose the actual price, but it is definitely a lot cheaper.
Definitely! The core of our product is software so ideally we just sell software licenses (much higher margins). Turns out there are a lot of drone companies that want a plug and play product though, and don't have spare processing power around to run our software.
