AI-powered data analytics for airports, Google reveals Gemini details, Dashboards for marketing

• Vendor news
• In the airfields
• On the road
• In today’s news
• In the international scene
• It's party time!

Lots of news from technology vendors and modern cases on how to use data analytics for operations excellence – this is what March brought us this year.

Vendor news

Komodo Health has unveiled a new self-service application designed for health research teams with no coding experience. MapView is the first major application debuting on overarching platform MapLab, unveiled last year to generate insights into disease trends, treatment pathways, patient populations and other complex questions. MapLab integrates Komodo’s de-identified Healthcare Map on more than 330 million patient journeys. The new offering, MapView, is designed as a no-code, self-service application that helps users visualize complex healthcare research questions with no technical expertise needed. It includes templates tailored to a variety of use cases and allows users to upload and integrate custom data sets for further insights.

Funnel launched its new visualization feature, Funnel Dashboards, enabling marketers to find deviations and patterns in their data much more efficiently than any existing third-party tools and plug-ins. Funnel Dashboards were designed specifically with marketers in mind, offering them unparalleled visualization speed and reliability without the weight of BI or IT features that they never use. This new frictionless data exploration is part of cementing Funnel as the leading marketing intelligence solution. Funnel helps marketers to connect all of the performance data from disparate platforms and normalize that data in order to surface insights that can drive business performance. On average today, small- and medium-sized businesses manage marketing activities across approximately eight different platforms, leading to 65 unique data sources. Marketers must balance the need for sturdier tools to handle this data volume against the practical requirements that they own responsibility for that data.

Autonomous mobile robots (AMRs) provider Locus Robotics launched its business intelligence tool LocusHub, enabling customers to leverage reporting tools and data insights to make recommendations to fleets of AMRs. LocusOne coordinates the company’s AMRs, known as LocusBots. The system integrates with warehouse management systems and provides over-the-air updates for continuous learning and improvement of the AMRs’ functionality. LocusHub will serve as the AMRs’ operations management solution, providing real-time reporting on the AMRs’ performance toward optimization performance metrics set by customers. The management tool will enable warehouse managers to set AMRs’ workflow routing, use machine learning to forecast staffing needs and order volumes, identify workflow bottlenecks, and set permission-based access and parameters for staff based on their role specifications.

Meanwhile Google revealed the details of Gemini, Google’s long-promised, next-gen GenAI model family. It comes in three flavors: Gemini Ultra, the flagship Gemini model, Gemini Pro, a “lite” Gemini model, and Gemini Nano, a smaller “distilled” model that runs on mobile devices. All Gemini models were trained to be “natively multimodal” — in other words, able to work with and use more than just words. They were pretrained and fine-tuned on a variety of audio, images and videos, a large set of codebases and text in different languages. This sets Gemini apart from models such as Google’s own LaMDA, which was trained exclusively on text data. LaMDA can’t understand or generate anything other than text (e.g., essays, email drafts), but that isn’t the case with Gemini models.

South Korea’s LG Uplus Corp. announced that it would introduce the smart customer support solution artificial intelligence Callbot to the call centers of domestic home appliance maker Cuckoo Electronics and its rental arm Cuckoo Homesys. AI Callbot is a voice-based AI assistant. It's a part of LG Uplus's structured AI contact center (AICC) system, U+AICC On-Premise. It can handle customer inquiries like after-sales service registration and guide them to nearby repair centers. This AI solution helps manage customers who purchase products online, similar to those who buy through home shopping channels. LG Uplus reports impressive results from a one-month pilot program at the Cuckoo call center.

In the airfields

Sydney Airport unveiled the details of their project for accelerating the airport’s long-term data strategy. This strategy included harnessing real-time data to streamline airport resource management, monitor airport capacity and enhance the passenger experience. The objective was to provide deeper insights into the breadth of airport operations – from kerbside drop-off, to check-in, to baggage drop, to immigration – to deliver a seamless customer experience. Sydney Airport partnered with Bi3 Technologies and the Microsoft Data & AI team to undertake a scope of work that would help achieve this goal. The first phase of the scope of work was to build a new data analytics platform that would streamline and modernize the airport’s data ingestion processes to support strategic decision-making. The second phase included creating an Operational Dashboard that harnessed AI and machine learning to enhance the passenger experience. Built within the Microsoft Azure ecosystem, the two phases of work would unlock the visibility, efficiency, and flexibility of real-time data at Sydney Airport. The new data platform relied on a ‘plug-and-play’ approach, providing the Sydney Airport team with a holistic, real-time data estate at their fingertips. With the platform configured to optimize data streaming, capturing data in real-time allows the airport to democratize data so it can be accessed for various scenarios, such as asset tracking, customer experience, quality control, health and safety.

Another airport, another success story. Copenhagen Airport, the biggest and busiest airport in Scandinavia, reports the first results of its airport-wide AI-powered data analytics and intelligence project. The aim was to significantly increase the airport’s maximum passenger capacity and create new opportunities for airport mapping by integrating huge amounts of data on traffic handling, flight times, check-in and security to optimize processes. The airport lacked a central ecosystem that could provide the operational traffic system and modern, technology focused data and intelligence support needed for holistic optimization. Project AIRHART has enhanced aiport’s handling of the huge amount of data needed to run the very complex operation of the airport, involving a large number of stakeholders including air traffic control, airlines and ground handlers. They can now optimize our turnaround times for airlines and handlers, improving total turnaround and travel time for passengers, but also reduce CO2 emissions while aircrafts are parked, landing or taking off in Copenhagen. For example, the airport can use business intelligence to ensure that aircraft are only cleared for taxiing once the team is sure they won’t be parked on the apron, using unnecessary fuel. Likewise, it has a more efficient, automated process for verifying and linking key flight information, which was previously handled manually, as well as sharing information with the network of airports it collaborates with.

On the road

Australia’s largest freight rail operator, Aurizon, plays a key role in underpinning Australia’s export and trades, powering resource-intensive industries like mining, and supporting the nation’s supply chain resilience. To play this role effectively, Aurizon was looking to its data to inform how it develops capabilities and strategies that can ensure efficiency and sustainability. Aurizon’s fleet of locomotives is over 700 strong, with nearly 400 of those now fitted with sensors that relay telemetry data back to Fabric in real-time. The majority of these locomotives send 1,000 channels of data per second, which equates to nearly 250 gigabytes of this data collected every day. To help it make full use of this new influx of data, Aurizon has developed a three-year modernization project to reimagine its entire analytics platform. It is focused on combining its enterprise and operational data with real-time condition sensor data to supercharge the value it can get out of its data. A significant percentage of Aurizon’s cost base is associated with buying and maintaining assets. Leveraging data and analytics to increase efficiency around maintenance is a critical element of its cost-saving strategy. Its data now integrated in Microsoft Fabric, also presents many opportunities for optimization around crew rostering, yard management, scheduling and daily operations.

In today’s news

Thomson Reuters, a media conglomerate, has announced it would invest $8 billion in artificial intelligence. The company also aims to spend upwards of $100 million to develop its own AI tech each year for its customers in the legal and accounting professions. the company last year finished a two-year effort to change from a content provider into a “content-driven” tech company. Generative AI came along soon after, presenting another opportunity to transform. Thomson Reuters in November debuted a series of generative AI initiatives aimed at transforming the legal profession, offering lawyers tools to enhance their research and workflow. Among them was the addition of GenAI to the AI-Assisted Research on Westlaw Precision platform, letting legal professionals quickly find answers to complex research questions.

In the international scene

Interestingly, a few more countries would like to jump into the burgeoning AI market. Thailand, for example, has announced that the country required some 100,000 experts for artificial intelligence-related jobs. However, the country only has some 21,000 AI experts at present. That is why the government seeks to launch a special visa procedure for AI experts and people with advanced computer skills under a so-called Global Digital Talent Visa project. The Thailand’s government will also study the European Union’s new Artificial Intelligence Act and use its guidelines on AI development to boost Thailand’s digital economy and help turn it into a regional digital hub. The government will also set up a subcommittee under the National AI Committee. The subcommittee will be in charge of implementing AI policies, so Thailand has a clear operational plan for investing in AI infrastructure, such as building data centres, cloud centres and high-performance computers. The AI industry in Thailand will focus on developing deep tech and a language model based on the Thai language.

The government of Saudi Arabia plans to create a fund of about $40 billion to invest in artificial intelligence. The planned tech fund would make Saudi Arabia the world’s largest investor in artificial intelligence. It would also showcase the oil-rich nation’s global business ambitions as well as its efforts to diversify its economy and establish itself as a more influential player in geopolitics. The Middle Eastern nation is pursuing those goals through its sovereign wealth fund, which has assets of more than $900 billion. The $40 billion target would dwarf the typical amounts raised by U.S. venture capital firms and would be eclipsed only by SoftBank, the Japanese conglomerate that has long been the world’s largest investor in start-ups.

The best use of AI can be seen in a tiny Caribbean Island of Anguilla. In Anguilla, east of Puerto Rico, the AI boom has made the country a fortune. The British territory collects a fee from every registration for internet addresses that end in “.ai,” which happens to be the domain name assigned to the island, like “.fr” for France and “.jp” for Japan. With companies wanting internet addresses that communicate they are at the forefront of the AI boom — like Elon Musk’s X.ai website for his artificial intelligence company — Anguilla has recently received a huge influx in requests for domain names. For each domain registration, Anguilla’s government gets anywhere from $140 to thousands of dollars from website names sold at auctions, according government data. Last year, Anguilla’s government made about $32 million from those fees. That amounted to more than 10 percent of GDP for the territory of almost 16,000 people and 35 square miles. Anguilla’s control of .ai dates back to the early days of the internet, when nations and territories were assigned their slice of cyberspace. Anguilla received .ai, and its government, whose own site is www.gov.ai., did not make much of it until the domain names started bringing in millions. Officials are uncertain how long the boom will last, but they predicted 2024 would bring in similar income as last year from domain names.

It's party time!