Release Date: July 29, 2024
For the complete transcript of the earnings call, please refer to the full earnings call transcript.
Positive Points
- SES AI Corp (SES, Financial) is on track to complete its B-Sample joint development partnership with Hyundai by the fourth quarter of this year, which will yield one of the largest capacity lithium metal lines globally.
- The company has successfully integrated AI into its operations, including design, technology development, manufacturing, and aftermarket support, which is expected to accelerate the commercialization of next-gen battery technologies.
- SES AI Corp (SES) has developed AI solutions for manufacturing, safety, and science, which are expected to significantly reduce the time required for large-scale commercialization of next-gen battery technologies.
- The company has entered the air mobility market, including urban air mobility (UAM) and drones, and is seeing strong demand in these sectors.
- SES AI Corp (SES) ended the second quarter with $294.7 million in liquidity and has updated its full-year 2024 guidance to reflect more prudent cash management, expecting total cash usage to be in the range of $100 million to $120 million.
Negative Points
- The traditional human-based approach to optimizing cell design and manufacturing quality is slow, taking at least eight years, which SES AI Corp (SES) aims to overcome with AI.
- The company faces significant competition from incumbent battery players who dominate the global market, making it challenging for next-gen battery companies to become relevant.
- SES AI Corp (SES) is heavily reliant on AI for its future growth and commercialization, which carries risks if the AI solutions do not perform as expected.
- The company is investing heavily in AI and new battery technologies, which could strain its financial resources if the expected revenue streams do not materialize.
- There are uncertainties and risks associated with the integration of AI into manufacturing and safety processes, which could impact the company's ability to deliver on its promises.
Q & A Highlights
Q: What incremental data have you seen on AI to push for this all-in approach?
A: Qichao Hu, CEO: We started working on AI for safety in 2017 and AI for manufacturing towards the end of A-sample. With more data, we found that AI models can recommend quality specs and identify relationships between manufacturing steps much faster than human engineers. For safety, AI models can predict incidents 10 to 30 cycles earlier than traditional methods. In AI for science, our models have already identified 17 new molecules, three of which are being tested and show promising results.
Q: How are EV OEM partners viewing AI for manufacturing and safety?
A: Qichao Hu, CEO: OEMs see AI as necessary to ensure the safety of new battery chemistries at commercial scale. It also helps them quickly gain proficiency in battery manufacturing and safety, which is crucial as they aim to control their own battery production, moving away from reliance on large battery manufacturers.
Q: How does the AI model expand to the lithium-ion industry and OEMs?
A: Qichao Hu, CEO: Our AI models are chemistry-agnostic and can be applied to next-gen lithium-ion batteries. For example, a company commercializing silicon lithium-ion batteries can use our AI for manufacturing to optimize quality specs. Similarly, AI for safety can be used to monitor and predict the health of lithium-ion cells in vehicles.
Q: How will the AI solutions be monetized outside of SES's own manufacturing?
A: Qichao Hu, CEO: Initially, we will fine-tune our models with data provided by partners for free. Once optimized, we will license the models. AI for safety could be priced as a premium per vehicle per month over the warranty period, while AI for manufacturing could be a fee per line per year.
Q: Will SES own the IP generated from AI solutions?
A: Qichao Hu, CEO: Yes, we will own the models and may open-source parts to accelerate development. For AI for science, the molecular property database will be open-source, but new molecules generated by our models will be proprietary IP.
Q: Can AI be both proactive and reactive in solving manufacturing and safety issues?
A: Qichao Hu, CEO: Yes, in manufacturing, AI can recommend quality specs and identify steps to improve. For safety, AI will monitor health and predict incidents, but the OEMs will decide how to act on these predictions.
For the complete transcript of the earnings call, please refer to the full earnings call transcript.
