People love saying that generative AI (gen AI) will transform the maritime ecosystem, but often they overlook a critical aspect needed to make that happen. Windward’s recent webinar featuring two Amazon Web Services (AWS) experts, plus our co-founder and CEO, dove deep on the differentiator you need to really reap the benefits.
The panelists also looked at the state of the supply chain/logistics industry in 2024 and how generative AI can help, plus Windward’s approach to data curation.
Missed the webinar? Watch it now.
AWS and Windward Experts at the Webinar
Speakers:
Data is the Differentiator
Vadim Tereshchuk, Solutions Architect at AWS, stressed that gen AI applications are just the tip of the iceberg, the part that customers see – but these applications are built on a lot of data behind the scenes.
“When you start speaking about gen AI, it’s all about the data,” added Eric Topp, Head of Worldwide Solutions & Strategy, Transportation & Logistics, AWS. “There’s this big rush to do something with gen AI from leadership, but if you don’t have the right foundation and cleanse your data, harmonize it, and hydrate your data lake properly, you can take a really good gen AI application and turn it into something that’s worthless, because your data is not good. You can ask a question, and you’ll get an answer. It just might not be the right answer because the data is incorrect.”
Ami Daniel, Windward Co-Founder and CEO at Windward, explained why a top–down approach is now needed.
“In the shipping world, people have been buying data from companies that are, in essence, selling third-party data. The gen AI conversation flips this story on its head. It makes the corporates start from their applications, their data lakes, and their needs and talk to people like Windward, versus just asking which data can you give me, or can you just tell me where this ship is going or where this cargo is going or where this container is going…the focus is less on which data we can buy and more on what problem we trying to solve.”
Effective gen AI results for maritime and supply chain aren’t going to come from a plug-and-play approach.
“Gen AI foundation models aren’t a one-size-fits-all solution. Sometimes, just adding your data to the models gives great results. Sometimes, it’s not enough, and we need to fine-tune the models or continuously pre-train them to greatly improve our results. It requires more effort, research, and optimization, and then they will give great results,” said Vadim.
Structured vs. Unstructured Data & Expert Oversight
Should organizations be worried about structured vs. unstructured data?
“Gen AI models can work with most structured and unstructured data. Structured data is like what you get from a database, and it’s well-defined. Unstructured data is just text documents, contracts…both of them can be used to enhance gen AI and get better results,” said Vadim.
“If we take unstructured data, we add it to our vector database and integrate this vector database with our gen AI model using embedding models, then we can filter and extract relevant data from RAG (Retrieval Augmented Generation), from those text documents previously unstructured, and augment our prompts with it and get better results from our LLM model. This is a great way to use unstructured data.”
All speakers stressed the need for human oversight to manage AI reliability and prevent issues such as data hallucination. They also highlighted the role of partnerships with AI specialists, such as Windward, in effectively navigating these complexities.
State of the Supply Chain/Logistics Industry in 2024
Eric presented an interesting overview of where the industry stands. The state of the maritime and logistics industry is dynamic. Shipping costs have fluctuated significantly over the past three years due to various factors. There are labor shortages and the demand for skilled professionals knowledgeable in gen AI and data lakes has surged. Clients are increasingly interested in applications such as those offered by Windward to enhance resiliency and reduce risk in operations.
Windward’s recent blog post explains some interesting gen AI use cases that can help improve the current state of affairs for supply chain organizations.
Recommended Approaches and Best Practices
When advising clients, Eric recommends a cautious approach to adopting gen AI. Starting small and scaling gradually allows companies to integrate AI effectively, without overwhelming their existing systems. Despite the excitement around gen AI, many clients are still focused on traditional AI and machine learning, underscoring the importance of a measured and strategic implementation of new technologies.
Ami detailed Windward’s approach to data curation. It emerged from the realization that automating everything was not only costly but also lengthy, due to numerous edge cases. Initially, the company aimed for complete automation, but practical challenges, such as inconsistent data from carriers, led to customer dissatisfaction and churn.
This epiphany led Windward to emphasize the importance of curated data, combining domain knowledge and advanced technology. Instead of relying solely on raw data, Windward uses labeled datasets, customer data, and quality assurance processes to train our vertical AI models. This method ensures higher accuracy and reliability, meeting the detailed demands of the maritime industry.
The maritime industry stands on the cusp of significant transformation driven by gen AI. By focusing on accurate data management and building strong partnerships with AI specialists, maritime orgs, and supply chain/logistics companies can navigate the complexities of AI integration and unlock new levels of efficiency and resilience in their operations.
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