Latest news with #data
CNN
an hour ago
- Business
- CNN
Business owners confront masked agents detaining gardener
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Arab News
a day ago
- Business
- Arab News
Saudi Arabia highlights roles of data, AI in achieving UN goals
RIYADH: The Saudi Data and AI Authority has highlighted the Kingdom's efforts to use data and artificial intelligence in support of the UN's 2030 Sustainable Development Goals, the Saudi Press Agency reported on Saturday. The authority participated in the 22nd session of the UN High-Level Committee on South-South Cooperation, which was held May 27-30, with a presentation titled 'Leveraging Science, Technology, and Innovation.' The Saudi delegation was led by representatives of the Ministry of Economy and Planning and included members of the Ministry of Foreign Affairs, the Ministry of Communications and Information Technology, and the Saudi Fund for Development. The authority 'showcased its expertise in developing AI- and big data-based digital solutions that enhance decision-making and support international efforts to achieve comprehensive, sustainable development — especially in developing countries — through integrated, innovation-driven technological systems,' according to the SPA, which added that the authority's participation 'reflects Saudi Arabia's leading role in collaborating with international organizations and governments to exchange successful experiences in data and AI,' and 'aligns with the goals of Saudi Vision 2030 and strengthens the Kingdom's presence as in global forums as an active partner in shaping the future of AI.' Earlier this month, the authority was honored by Arab League Secretary-General Ahmed Aboul Gheit during the digital commerce exhibition Seamless Middle East in Dubai for its role in advancing Saudi Arabia's data and AI sector and accelerating digital transformation. The authority has expanded AI adoption across key sectors, 'improving government service efficiency and driving sustainable development through innovative initiatives,' the SPA stated. 'By advancing data and AI and building national capabilities, the authority has positioned Saudi Arabia among global AI leaders, supporting Vision 2030's digital economy and knowledge society goals.'
Globe and Mail
a day ago
- Business
- Globe and Mail
Quant Signals Point to High-Probability Trades in UNH, CVX and SOUN This Week
In the film 'Enemy at the Gates,' an early scene set in the midst of the Battle of Stalingrad shows the classic Soviet meatgrinder attack: essentially, it's an attempt to overrun enemy positions with massive scale, irrespective of the cost. Because this brute Russian logic applies throughout the underlying society, it's a human rights catastrophe. But applied to data? The statistical implications are impregnable and that's the beauty of the Playmaker forecasting model I've been using over the past month-and-a-half period. Fundamentally, the discipline of trading — specifically options trading — focuses on probabilities. Because the framework is short term and defined, the emphasis is less on the 'why' of a particular asset or security and more on the 'how': how much, how fast and, most importantly, how likely. Generally, there are two ways of approaching the probabilistic dilemma. The standard American or western approach is to attempt to find signals and patterns in the continuous scalar signal that is the share price. Here, stochastic calculus and partial derivatives are deployed to estimate future price ranges. However, with the advent of artificial intelligence, analysts no longer need to estimate probabilities; they can directly count the datapoints in brute fashion at blistering scale and speed. But in order to make data comparisons across vast ranges of time, it's important to compress this demand profile into its most elemental, binary form. And that's what the Playmaker does, count tens of thousands of market breadth datapoints — or sequences of accumulation and distribution — to identify highly probabilistic trades. I'm not here to tell you why I think these stocks may move higher. Frankly, that's irrelevant. No, I'm letting the data guide the discourse. Below are three stocks to put on your watchlist for the coming week. UnitedHealth (UNH) Let's start with a controversial idea in the form of UnitedHealth (UNH). The healthcare giant has just about hit every branch of the ugly tree. You don't need me to rehash the same tired narratives. What you might not be aware of is that from a market breadth perspective, UNH stock may be signaling a reversal pattern. In the past two months, UNH stock has printed a '4-6-D' sequence: four up weeks, six down weeks, with a net negative trajectory across the 10-week period. In 66% of cases, the following week's price action results in upside, with a median return of 2.88%. Should the 4-6-D sequence pan out as projected, UNH stock could potentially reach over $310 within a week or two. What makes this setup so intriguing is that, as a baseline, the chance that a long position will be profitable over any given week is only 54.49%. Therefore, the 4-6-D shifts the odds firmly in favor of the bullish speculator. With the above market intelligence in mind, I'm looking at the 305/310 bull call spread expiring June 20. This transaction involves buying the $305 call and simultaneously selling the $310 call, for a net debit paid of $260. Should UNH stock rise through the short strike price at expiration, the maximum reward is $240, or a payout of over 92%. Chevron (CVX) Thanks to widescale societal changes combined with economic challenges, circumstances have not been favorable for the oil industry. Since the start of the year, supermajor Chevron (CVX) has struggled for traction, with CVX stock losing almost 6%. For context, the benchmark S&P 500 — which isn't exactly storming up the charts — is up half-a-percent. Still, market breadth data provides a different impression of the hydrocarbon juggernaut. In the past two months, CVX stock printed a 3-7-D sequence: three up weeks, seven down weeks, with a net negative trajectory across the 10-week period. Notably, this relatively rare pattern generates a 70.27% probability that the following week's price action will rise, with a median return of 2.6%. On Friday, CVX stock closed at $136.70. If the implications of the 3-7-D pan out predictably, it may soon reach over $140. Now, Chevron exemplifies why a Barchart Premier membership is worth its weight in gold. With Premier access, traders can drill down the available bull spreads for the June 20 expiration date. Specifically, the 138/140 bull spread is enticing because $140 is a legitimately rational target and the payout is robust at over 104%. In my opinion, the aforementioned spread is favorably mispriced. SoundHound AI (SOUN) I don't mean to rehash an idea that I already discussed just a few weeks ago. Still, SoundHound AI (SOUN) is awfully intriguing because of its relatively low share price and high popularity among retail traders. This presents on occasion a favorably combustible mix that, if timed correctly, could generate significant gains in a short period. A few weeks ago, I mentioned that SOUN stock had printed a 3-7-D sequence: three up weeks, seven down weeks, with a net negative trajectory across the 10-week period. At the time, I mentioned that the pattern generated a 58.33% probability that the following week's price action will result in upside, with a median return of 13.58%. This time around, we're back at a similar juncture with a 3-7 sequence. However, the twist is that the 10-week period has resulted in a positive trajectory. The 'U' iteration of the 3-7 has materialized only six times since SoundHound's public market debut. And in all six cases, the following week's price action swung higher, with a median return of 15.08%. Generally, I take 100% success ratios with a huge grain of salt. Still, the 3-7 sequence, whether of the up or down variety, ultimately favors the bulls. If you're willing to play the numbers game, the 10/11 bull call spread expiring June 20 is awfully tempting.
Wall Street Journal
2 days ago
- Business
- Wall Street Journal
It's Waymo's World. We're All Just Riding in It.
The website of the California Public Utilities Commission is not the first place you would go looking for signs of progress in one of the world's sexiest industries. But every few months, this agency tasked with regulating passenger transportation publishes a bunch of spreadsheets with valuable information about self-driving cars and how many people are riding in them. And in the latest data that was recently dumped online, there was a telling update about a company identified simply as PSG0038152.
Forbes
2 days ago
- Business
- Forbes
Act On Data Faster: AI At The Edge
How AI at the edge helps you unlock the value of data with speed, scale and security. Data isn't just everywhere — it's everything. Yet many organizations struggle to harness its full potential. The answer? Edge AI. The edge is where data originates, decisions happen in real time, and innovation takes flight. Organizations with edge operations that embrace AI today will shape a smarter, more connected tomorrow by acting instantly on data where it's created. It is predicted that edge AI addressable revenue will reach $157 billion by 20301, so it should be no surprise that organizations in industries such as manufacturing, healthcare, retail and more are seeking ways to use AI at the edge to make better, faster, data-driven decisions. However, to fully leverage the potential of edge AI, it's critical to begin by aligning edge AI use cases with your strategic goals. So, where do you begin? Start by defining the problem edge AI can solve for your organization, such as improving operational efficiency, enhancing customer experiences or mitigating risk. This could involve leveraging enabling technologies like computer vision to achieve outcomes such as predictive maintenance, enhanced healthcare diagnostics, or personalized marketing. Once you've selected your use case, the next step is to determine the technology requirements and allocate resources and budget to your initiative. Finally, you'll want to work with one or more trusted partners to build a scalable foundation that is optimized for edge environments and can adapt to future demands and the continuous evolution of AI technologies. As you work to bring intelligence closer to the point of action, you're likely to encounter a range of complex challenges. When designing your AI foundation, be sure to include considerations such as: When it comes to AI success at the edge, three factors stand out: speed, scale, and security. Together, they form the foundation for unleashing AI's full potential. Speed: Accelerate action. Data generation is soaring, especially at the edge. It takes time to send data to core data centers and cloud environments, which can lead to a lag in processing real-time demands. Edge computing changes the game by processing data where it's created, eliminating latency and enabling decisions in milliseconds. Combined with AI, it has the potential to drive smarter operations and predictive insights, empowering industries to lead with agility and innovation, processing data where it's created unlocks truly real-time action – enabling 'agentic' responses vital for everything from mitigating risks in healthcare to optimizing energy grids or boosting manufacturing efficiency, reacting instantly rather than waiting for post-processing. This speed empowers industries to lead with agility and innovation. Scale: Meet growing data demands. Of course, edge AI success isn't just about speed — it's also about scaling to handle massive amounts of data. Traditional centralized IT models struggle with the complexity of distributed operations, but thoughtfully planned and flexible edge AI means deploying intelligent systems close to where actions happen. This approach leads to efficient, synchronized operations across locations, adapts to growth in real-time, and simplifies the process of replicating successful models throughout additional locations. By solving for scalability, you can unlock agility and thrive in dynamic markets. Security: Protecting data at the edge. Sensitive data demands uncompromising security, but the distributed nature of edge environments introduces vulnerabilities. Edge AI can enhance security by keeping sensitive data local, reducing reliance on centralized systems and minimizing exposure to cyber threats. This localized approach also simplifies regulatory compliance including regulations such as the general data protection regulation (GDPR) and aligns with data sovereignty standards. By integrating encryption and zero trust principles, your organization benefits from resilience and safeguards critical assets right where the data is generated and processed. Coordinating IT operations across data centers, clouds, factories, retail outlets, remote sites, and more can be overwhelming without the right tools. To simplify operations, your edge AI solution should provide centralized management and orchestration capabilities for consistency and efficiency across distributed environments. By automating processes and seamlessly integrating workloads, you can reduce complexity, save time, and focus on innovation. Crucially, these tools must also facilitate the secure, end-to-end management of continuously evolving AI models and software stacks, adapting to new requirements and updates efficiently across potentially vast, distributed environments. Successfully addressing edge AI challenges and deploying solutions that meet the key requirements of speed, scale, and security requires a thoughtful, strategic approach with tools and frameworks designed specifically for each unique edge environment. Dell is uniquely suited to help you optimize edge AI workloads and deliver faster insights. For example, the Dell AI Factory with NVIDIA speeds AI adoption by delivering integrated Dell and NVIDIA capabilities to accelerate your AI-powered use cases, streamline your data and workflows and enable you to design your own AI journey for repeatable, scalable outcomes. In a recent survey by TechTarget's Enterprise Strategy Group, 91% of organizations believe they would benefit from more consistency in edge application and infrastructure management.2 Dell NativeEdge brings the power of Dell AI Factory with NVIDIA to the edge by enabling organizations to securely scale their infrastructure and orchestrate AI applications across any location. Support for virtualized and containerized environments is seamless, while NativeEdge Blueprints automate the deployment of frameworks and applications for faster, more efficient AI innovations. Designed to simplify and accelerate the deployment and management of AI at the edge, this 'one-click' approach to deploying and maintaining distributed edge solutions significantly reduces manual effort, complexity, and risk, allowing organizations to quickly adapt to evolving AI technologies and maximize their ROI by getting AI operational faster. To learn more about how to power your purpose with edge AI, read the eBook: Accelerating the Future with Edge Computing and AI.
