Latest news with #RajeshSubramaniam
Forbes
28-04-2025
- Business
- Forbes
The Zoo Revolution: Why Pretrained Models Are The Key To Scalable Edge AI
Rajesh Subramaniam is Founder and CEO of embedUR systems. From IoT and robotics to industrial automation and smart devices, AI is fundamentally changing how machines operate. But one of the biggest hurdles to widespread adoption has always been the complexity of building, training and deploying AI models—especially on the edge. That's where pretrained models come in. These ready-to-use tools are making AI faster, cheaper and more scalable. The rise of AI model zoos—curated collections of pre-built, optimized models—is the key to this transformation. Think of model zoos as an app store for AI that gives developers access to powerful AI capabilities (working models, curated datasets, blueprints) without a steep learning curve, extensive training, or deep technical expertise. For many businesses, training an AI model from scratch is not practical due to cost or time constraints. Even before building a product, teams must validate feasibility, which is often the costliest step. Pretrained models can accelerate this process by enabling rapid testing of multiple ideas to see which are viable before committing resources. Instead of spending months developing a proprietary model, companies can take an existing model from a model zoo, fine-tune it for their specific needs and deploy it rapidly—especially in cloud environments where models can run with minimal changes. On edge devices, deployment is more complex and often requires additional porting and optimization for each hardware platform. Small, low-power IoT devices at the edge need models that are both lightweight and efficient. Pretrained models have already been optimized for real-world applications; some are stripped-down versions of larger networks, making them ideal for quick prototyping on tools like Raspberry Pi. But in production, these models can be deployed on advanced, AI-native chips from vendors like Synaptics, STMicroelectronics and Silicon Labs, designed specifically for edge inference on a single chip. Traditionally, many of these small, low-power devices rely on cloud connectivity to make intelligent decisions. But running pretrained models directly on edge devices can reduce latency, improve reliability and conserve power. Developing high-performance AI for edge devices comes with enormous challenges. First, curating high-quality, relevant datasets is crucial. AI is only as good as the data it's trained on. This is especially important for edge AI, where a bad model can result in significant failures—for example, a facial recognition model that isn't trained on a diverse set of faces, lighting conditions and environments. Businesses that want to deploy AI need to make sure their datasets are well-curated, balanced and representative of actual use cases. Equally important is code and model efficiency. Edge devices operate under tight constraints: limited memory, storage, processing power, and often battery life. Unlike cloud environments, where inefficient code can be masked by throwing more compute at the problem, we don't have this luxury with edge AI. You can't afford bloated models with 20% waste. On the edge, there's no tolerance for inefficiency and no room for error. Every line of code and every model parameter has to be optimized. In cloud-based AI, an accuracy rate of 95% is often considered acceptable. But in edge AI, where devices have to operate independently with minimal errors, this isn't enough. For instance, it's not OK if a self-driving car fails to detect pedestrians in one out of every 20 trips. Achieving a required accuracy of 99% and above requires extensive testing and iterative improvements. The next five years will bring a wave of intelligent edge devices replacing traditional electronics. These AI-powered systems will be smaller, more energy-efficient and capable of making real-time decisions without relying on cloud connectivity. This shift will affect every industry that relies on connected devices, from smart homes to industrial automation. But there's an important dynamic that's often overlooked: product life cycles are shrinking. Over the past decade, for example, hard drives have evolved every few months instead of every few years. The same will apply to AI-powered devices. Products considered bleeding-edge today could be obsolete within months or a year, replaced by newer, more advanced alternatives. That means companies will need tools that can help them get new products to market fast and adapt to changing technologies as quickly as possible. Pretrained models and model zoos will be crucial in this race. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Yahoo
30-03-2025
- Business
- Yahoo
FedEx Stock Hits 52-Week Low. Is the Dividend Stock a Buy Now?
FedEx (NYSE: FDX) hit a 52-week low on March 21 after reporting earnings and slashing its full-year guidance. However, the stock has since recovered nearly all of the losses from that sell-off -- although FedEx is still down over 14% in the past year at the time of this writing. Here's what's driving FedEx's guidance cut and if the dividend stock is worth buying now. FedEx has made significant progress in cutting costs and improving its operations, which has helped operating income grow faster than revenue. At the end of 2022, FedEx unveiled its DRIVE program, hosting an investor presentation in April 2023. In the presentation, FedEx said it had identified roughly $4 billion in value and savings that could be achieved by fiscal 2025. Additionally, its Network 2.0 program would generate another $2 billion in value by fiscal 2027. Network 2.0 aims to combine FedEx's Express segment with its ground division to create a more streamlined network. In its latest earnings announcement (third-quarter fiscal 2025), FedEx reiterated its full-year fiscal 2025 target of $2.2 billion in permanent cost reductions from its DRIVE program -- including $600 million in savings from the recent quarter -- building upon progress made in fiscal 2024. FedEx first provided the $2.2 billion target last June, so reaffirming the guidance is an encouraging sign that DRIVE is succeeding. However, FedEx's earnings forecast has not stayed consistent. In June, FedEx forecast $20 to $22 in adjusted fiscal 2025 earnings per share (EPS), cut the guidance to $19 to $20 per share in December, and then just reduced the guidance again down to $18 to $18.60 per share. Weaker economic expectations are to blame for the reduced guidance. Trade tensions weren't defined when FedEx reported second-quarter fiscal 2025 earnings in December. Now, the company could see pricing pressure and cost inflation from tariffs, which could slow transportation volumes. On the latest earnings call, FedEx said that many of its customers are already anticipating price increases, which could justify a price increase from FedEx to help offset costs. FedEx has done a good job capturing demand surcharge pricing. Timely deliveries, paired with DRIVE cost reductions, could help protect FedEx's margins even during a challenging macro environment. FedEx is an international business, but it's worth noting that the majority of deliveries are in the U.S. FedEx CEO Rajesh Subramaniam said the following on the earnings call: As a reminder, in terms of our revenues split by geography, we serve an extremely diversified customer base across the more than 220 countries and territories. To put some numbers around this, taking our FY '25 revenue through the third quarter, nearly 75% comes from our U.S. domestic services. Another approximately 10% of our revenue comes from non-U.S. intra-country or intra-regional services. And from a bilateral U.S. trade perspective, our biggest single-country exposure represents only about 2.5% of total revenue. In sum, tariffs could be a thorn in FedEx's side, but it has the pricing power to help offset higher costs, and the bulk of its business is domestic. Analyst consensus estimates call for $18.20 in fiscal 2025 EPS and $21.09 in fiscal 2026 EPS. Based on a share price at the time of this writing of $241.07, FedEx would have a price-to-earnings (P/E) ratio of just 13.2 based on fiscal 2025 guidance and 11.4 based on fiscal 2026 results. That's dirt cheap compared to FedEx's 10-year median P/E of 18.4. Granted, investors may want to assume that FedEx's earnings are less than currently expected if trade tensions ramp up and impact delivery volumes. FedEx pays a stable and growing dividend of $5.52 at the time of this writing -- good for a yield of 2.3%. The dividend is affordable even if earnings come down, so investors can count on FedEx for passive income. Transportation companies can go through cycles based on economic growth and trade. Tariffs inherently make trade more difficult, which is bad for FedEx. However, long-term investors shouldn't get too bogged down by economic cycles or trade policy. FedEx has done an excellent job with its cost-cutting efforts. The company generates strong cash flow to continue funding long-term investments in Network 2.0 and other projects despite a cyclical downturn. All told, FedEx remains a well-rounded value stock to buy now. Before you buy stock in FedEx, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and FedEx wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $682,965!* Now, it's worth noting Stock Advisor's total average return is 842% — a market-crushing outperformance compared to 165% for the S&P 500. Don't miss out on the latest top 10 list, available when you join . See the 10 stocks » *Stock Advisor returns as of March 24, 2025 Daniel Foelber has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends FedEx. The Motley Fool has a disclosure policy. FedEx Stock Hits 52-Week Low. Is the Dividend Stock a Buy Now? was originally published by The Motley Fool Sign in to access your portfolio
