AI in Transportation – Tech | Business | Economy https://techeconomy.ng Tech | Business | Economy Thu, 10 Jul 2025 15:49:44 +0000 en-GB hourly 1 https://wordpress.org/?v=7.0 https://techeconomy.ng/wp-content/uploads/2025/06/cropped-256Px-32x32.png AI in Transportation – Tech | Business | Economy https://techeconomy.ng 32 32 Google Backs 17 Startups Tackling Real-World Problems with AI Tools, Funding https://techeconomy.ng/google-second-ai-academy-cohort-2025/ https://techeconomy.ng/google-second-ai-academy-cohort-2025/#respond Thu, 10 Jul 2025 15:49:44 +0000 https://techeconomy.ng/?p=162828 Google has named the second cohort of startups selected for its AI Academy American Infrastructure programme, backing 17 early-stage companies with funding, tools, and engineering support to help solve real-world challenges using artificial intelligence.

This four-month initiative, now in its second year, targets startups working in sectors such as cybersecurity, transportation, education, and healthcare. 

Google is not offering equity-based investments here, instead, it’s providing hands-on mentorship, sales training, and access to its cloud tools, including some of its most advanced AI models. Most of the sessions will be virtual, but participants will later gather in person for a summit.

These companies had to meet tight selection criteria: evidence of market traction, at least six months of financial runway, and a product or service capable of making significant impact. Applications closed in mid-May following a highly competitive process.

Startups selected for this new cohort include:

  1. Block Harbor, working on cybersecurity for automotive systems.
  2. Attuned Intelligence, building AI-powered voice agents for call centres.
  3. CloudRig, helping construction contractors manage production workflows with AI.
  4. Mpathic, automating clinical trials and medical documentation.
  5. StudyFetch, offering personalised learning tools to students and educators.
  6. Omnia Fishing, which gives users personalised fishing advice based on data.
  7. Making Space, matching disabled jobseekers with potential employers.
  8. Tansy AI, helping users organise their medical records and appointments.
  9. Waterplan, which lets companies track and respond to water-related risk.
  10. Nimblemind.ai, making health data more usable and searchable.
  11. Satlyt, a platform to process satellite data efficiently.
  12. Tradeverifyd, which helps companies assess supply chain risk in global markets.
  13. CircNova, using AI to understand RNA patterns for new therapeutics.
  14. Otrafy, automating supply chain compliance and documentation.
  15. Partsimony, helping companies build and manage their manufacturing supply chains.
  16. Vetr Health, providing at-home veterinary care.
  17. MedHaul, which connects hospitals with non-emergency transport options.

Among the programme’s earlier alumni is Cloverleaf AI, which secured a $2.8 million seed round after joining last year’s cohort. Another, Zordi, raised $20 million from Khlosa Ventures for its autonomous agtech solutions. These reveal Google’s reputation as an early identifier of high-impact startups in the AI space.

The Academy is just one of several efforts by the tech giant to shape the AI startup ecosystem. In May 2025, Google launched the AI Futures Fund, a rolling investment initiative supporting startups that are already building with DeepMind’s latest models—Gemini, Imagen, and Veo.

Startups funded under the Futures Fund receive equity investment, early access to the models, Google Cloud credits, and hands-on help from Google and DeepMind engineers. Some notable participants so far include:

  • Toonsutra, a comic app that uses Gemini to translate webtoons across multiple languages.
  • Viggle, an AI meme-generation platform powered by Gemini and Veo.
  • Rooms, which allows users to create 3D spaces with interactive avatars.

This expansion into targeted funding aligns with Google’s broader AI education and inclusion strategy. At the UN Summit of the Future, CEO Sundar Pichai announced a $120 million Global AI Opportunity Fund aimed at reducing what he called the “AI divide”, the growing disparity in access to AI knowledge and tools across countries. 

He said: “We believe AI should benefit everyone, everywhere, not just those in high-income economies.”

The $120 million fund works with NGOs and local partners to bring AI education to underserved communities, especially in countries with poor digital infrastructure or lacking policy frameworks to support tech growth.

Meanwhile, Google.org, Google’s charitable arm, has launched a $20 million Generative AI Accelerator that supports nonprofits using AI for public good. This includes funding for projects in climate resilience, healthcare access, and digital education.

These developments come as AI remains both a disruptive force and a promising tool. While the headlines usually focus on the risks, from deepfakes to disinformation, Google appears to be betting that the next breakthroughs will come from startups willing to solve practical, overlooked problems.

With its blend of funding, mentorship, and infrastructure support, Google is building a growing network of startups, and we see the company wants a hand in shaping how AI evolves far beyond Silicon Valley.

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Uber Freight Launches AI Tools to Tackle Supply Chain Challenges https://techeconomy.ng/uber-freight-launches-ai-tools/ https://techeconomy.ng/uber-freight-launches-ai-tools/#comments Wed, 21 May 2025 13:09:45 +0000 https://techeconomy.ng/?p=159171 Uber Freight, the logistics arm of Uber Technologies, has rolled out a comprehensive set of artificial intelligence tools designed to tackle one of the most challenging elements in business: supply chain logistics.

Having built a logistics-specific large language model embedded within Uber Freight’s transportation management system (TMS) and digital logistics platform, the company announced the launch of what it calls the world’s first scaled AI logistics network. 

This innovation, as we see it, aims to reframe how companies, including small businesses and Fortune 500 giants, approach freight, disruptions, and decision-making.

This is the inflection point we’ve been building toward,” said Lior Ron, founder and CEO of Uber Freight. “With the launch of our AI logistics network and reimagined TMS, we’re not just automating tasks—we’re enabling a new level of agility, foresight, and competitive advantage for our customers.”

Over the past year, Uber Freight has quietly tested its technology with select enterprise partners. Now it’s making it available globally. 

The suite includes over 30 AI agents that can autonomously handle procurement, tracking, payments, and analytics across the shipping lifecycle. These agents function in real-time, offering solutions, adjusting to disruptions, and predicting next steps before issues escalate.

By the end of 2025, Uber Freight says its TMS will evolve into what it calls a real-time logistics command centre, not just a system of record. 

With full integration of Insights AI and its AI agent ecosystem, the system aims to guide users with live data and automated decisions that would normally require hours of manual effort.

Colgate-Palmolive, a global consumer goods leader, has already seen good results. As one of Uber Freight’s flagship partners in its Design Partners Programme, the company has been using Insights AI within its logistics teams for a year.

Colgate-Palmolive is a caring, innovative growth company that is reimagining a healthier future for all. We advance our purpose by selling our essential health & hygiene products in more than 200 countries and territories, with a global supply chain to support this reach,” said Tatiana Martinez, vice president, North America Customer Service & Logistics, North America, Colgate-Palmolive. 

With the scale and complexity of our operations, the collaboration with Uber Freight on Insights AI has helped empower our team to access timely information, analyse our network, and make strategic decisions that drive faster growth. Insights AI has helped us plan with greater confidence and respond more effectively to disruptions, all in service of our ongoing commitment to customer centricity and operational efficiency.”

What’s unique here isn’t just the technology but the volume of freight it’s been applied to. Over $1.6 billion worth of goods moved through Uber Freight’s AI-powered infrastructure in just the last 12 months. 

The AI models backing this system have been trained on data from almost $20 billion in freight, including activity from one in three Fortune 500 companies.

Again, what’s different here is the model’s ability to interpret the nuance of logistics data. Uber Freight claims this isn’t generic automation, it’s a domain-specific system designed by logistics professionals who understand the volatility and timing of supply chain decisions.

Logistics is one of the most complex, data-rich industries on Earth, and it demands AI that’s purpose-built to understand it,” said Raj Subbiah, chief product officer of Uber Freight. “We built a domain-specific model that thinks like a logistics expert. That foundation enables us to proactively and continuously optimise our customers’ networks.”

Uber Freight’s journey started in 2017 as a simple broker between long-haul truckers and shippers. Today, it’s operating at a scale and complexity that few could have predicted. Its evolution into a full-service logistics intelligence provider has been steady, deliberate, and driven by years of embedded machine learning.

With Insights AI, customers can now pull up performance metrics, shipment patterns, and cost anomalies instantly. For example, you can ask the system to show all shipments made to CVS in 2023 or identify the worst-performing routes. What once took weeks and several layers of analysis can now be surfaced within seconds.

Ron explained: “Gain insights on your network much faster, at close to 100% accuracy instantly, versus formulating what you want to know, sending it to some analysts, and waiting for two weeks for the PowerPoint presentation to come back to have a discussion.”

For companies like Colgate-Palmolive, the AI system has already proven useful in flagging underperforming logistics partners. That insight allows them to take action immediately, either to resolve the issue or cut ties and shift strategy.

It’s a shift from reactive logistics to predictive operations. Alerts about overspending, inefficient routes, or delays can now land in a decision-maker’s inbox before the loss is incurred.

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