The Potential and Realities of AI: Bridging the Maturity Gap
Dr. Avital Schrift, VP of Core Technologies, Israel Aerospace Industries (IAI), at the Sparks Innovation Summit in Tel Aviv
Mandi Kogosowski
| 11/04/2024
“AI is everywhere in IAI. It is part of our avionics, communications, and cyber systems. It is employed, for example, in our health monitoring – predictive maintenance for aircraft and satellites. We deal with edge computing, single-agent and multi-agent autonomy, and with creating the manned/unmanned teams that will compose the future battlefield,” explained Dr. Avital Schrift, VP of Core Technologies, Israel Aerospace Industries (IAI), at the Sparks Innovation Summit in Tel Aviv this morning (Thursday).
Dr. Schrift then went on to discuss the maturity gap: bringing a lab-demonstrated AI system into being a truly operational, deployed and used system.
“In order to do so, we have to overcome several AI problems, the biggest ones being the trust and explainability issues. To persuade an operational user to actually use your system, you need to explain what the system is going to do in every possible scenario the customer may encounter, so that the customer is able to trust the system. We combine theory with simulations to achieve maximum results.”
Dr. Avital Schrift, VP of Core Technologies, Israel Aerospace Industries (IAI), at the Sparks Innovation Summit in Tel Aviv
“AI is everywhere in IAI. It is part of our avionics, communications, and cyber systems. It is employed, for example, in our health monitoring – predictive maintenance for aircraft and satellites. We deal with edge computing, single-agent and multi-agent autonomy, and with creating the manned/unmanned teams that will compose the future battlefield,” explained Dr. Avital Schrift, VP of Core Technologies, Israel Aerospace Industries (IAI), at the Sparks Innovation Summit in Tel Aviv this morning (Thursday).
Dr. Schrift then went on to discuss the maturity gap: bringing a lab-demonstrated AI system into being a truly operational, deployed and used system.
“In order to do so, we have to overcome several AI problems, the biggest ones being the trust and explainability issues. To persuade an operational user to actually use your system, you need to explain what the system is going to do in every possible scenario the customer may encounter, so that the customer is able to trust the system. We combine theory with simulations to achieve maximum results.”
