Latest news with #graphs
Scotsman
28-04-2025
- Business
- Scotsman
Why time in the market - not timing - matters most in investment planning
Time in the market | Thanawut - COMMENT Tom Ham CEO at Calton reassures 'it's time in the market, not timing the market' that's important Sign up to our daily newsletter – Regular news stories and round-ups from around Scotland direct to your inbox Sign up Thank you for signing up! Did you know with a Digital Subscription to The Scotsman, you can get unlimited access to the website including our premium content, as well as benefiting from fewer ads, loyalty rewards and much more. Learn More Sorry, there seem to be some issues. Please try again later. Submitting... I was heartened by interactions I had with clients in the aftermath of Trump's 'Liberation Day', the imposition of tariffs and subsequent market chaos. Despite the downward trending graphs, red-flashing Bloomberg terminals and images of people running across the New York trading floor, our phones weren't ringing off the hook. Tom Ham | Supplied I know anecdotally that other firms didn't have the same experience. I also know that one of the reasons lights weren't flashing at DEFCON 1here was that we have a consistent message around planning at Calton. Planning is the bedrock of everything we do. Planning is the dog that wags the investment tail. Planning is where we show our value as a not that I didn't speak to my clients that week. We were there for people who wanted reassurance. A long-time client called and began the conversation with, 'I already know what you're going to tell me, but I want you to tell me anyway.' This epitomises our service – long-term strategy, clarity of explanation, and we're there for you when you need what was the nugget of reassurance that my client needed to hear again? The classic investment axiom: 'It's time in the market, not timing the market.' Our long-term clients have become accustomed to hearing this. Most likely it came up in our first meeting and has become a bit of a jingle, but it's especially relevant when the markets take a 'time in the market' means is that you should aim to hold your investments for as long as possible –invest early, invest often –so that you maximise and compound your doing this, you are likely to encounter inevitable market dips. By staying invested throughout, you will benefit from the market's recovery by being there when the upswing starts. Attempting to 'time the market', by selling at the start of a dip or buying at the beginning of a recovery, could either crystallise your loss or lead to you missing the start of the recovery. It's a memorable phrase designed to help people avoid the knee-jerk reaction of selling everything off and converting to cash during a market fall. Data supports its wisdom. The markets do recover over time – that line keeps going up and to the right even if dips occur every five years or so. Equities have annualised a 10 per cent return over the past hundred years, despite wars, cycles of boom and bust, and the biggest upswings happen after the greatest falls, so if you look at how a portfolio fares with and without the best ten and 20 days of the past two decades you see that £100 invested in 2005 is now worth over £400, if you stay invested, but under £250 if you miss the best ten and under £200 if you miss the best 20 should bring greater nuance to this. For some clients, timing may be important and so we advise everyone to plan around this kind of market event. Anyone approaching retirement or already taking income will be justifiably apprehensive and will want clarity about how events in the US and global market will affect too early to answer that definitively but, in the meantime, we rely on planning. We advise clients to keep an emergency cash reserve to cover a minimum of six months' outgoings –or more, depending on their risk appetite – so they don't have to withdraw money in the most unfavourable circumstances. Another reassurance for clients is that our investment team's monthly bulletin in late 2024 warned of the gremlins that lay within US equities –over valuation and over concentration. Our portfolios managers have been on the front foot of this risk for some time, coming into 2025 with reduced allocations to US assets, in favour of the rest of the world. A bias that has considerably limited drawdowns this year in client portfolios. Our approach is one of proactivity rather than reactivity to give investors the best possible chance of achieving that 10 per cent annualised return from equities over the next decade. There are knowns and unknowns in this new Trump-shadowed world. This 90-day pause is not the end of the story. Further volatility is likely and there will be real effects for UK consumers, savers and investors if we enter a global recession. We will be here for our clients, to tell them something old or something new. Either way, planning will be front and centre.
Yahoo
25-04-2025
- Science
- Yahoo
World's largest solar telescope reveals unprecedented photo of the sun
When you buy through links on our articles, Future and its syndication partners may earn a commission. Weather on Earth can be wild, but it's not the only kind of weather we have to deal with. Space weather — all the winds and particles streaming off the sun — can have major impacts on Earth and human infrastructure. In the worst cases, this can mean dangerous disruption to our power grids and communications satellites. To help us predict these space storms, astronomers have a newly improved space weatherman — and it's the best one to date. The Daniel K. Inouye Solar Telescope (DKIST), perched atop the Hawaiian mountain of Haleakalā, is the world's largest telescope used for studying the sun and predicting these storms. The team behind this technological marvel recently hit a major milestone, finally turning on one of DKIST's most powerful cameras — known as the Visible Tunable Filter, or VTF — after more than a decade working on its creation. This camera is the final piece of the puzzle for DKIST, and the VTF's addition "will complete its initial arsenal of scientific instruments," Carrie Black, director of the National Solar Observatory, said in a statement. "The significance of the technological achievement is such that one could easily argue the VTF is the Inouye Solar Telescope's heart, and it is finally beating at its forever place," Matthias Schubert, project scientist for the VTF, said in the statement. VTF's first image shows a major clump of sunspots, dark blobs on the sun's surface caused by its intense magnetic field, each blob measuring wider than the continental United States. This impressive camera can see details down to a resolution of about 6.2 miles (10 kilometers) per pixel on the solar surface — an absolutely wild resolution given that the sun is tens of millions of miles away from us. Related: A mysterious, 100-year solar cycle may have just restarted — and it could mean decades of dangerous space weather VTF provides more than just a simple snapshot. It captures images at multiple wavelengths of light to measure a spectrum, while also gathering information on how the light's electric field is oriented (known as polarization). These extra perspectives on the sun help reveal details of the solar surface, magnetic field and plasma that are otherwise invisible, informing our predictions for space weather and solar flares. During just one observation of the sun, this instrument can collect more than 10 million spectra — graphs of the light's intensity over different wavelengths — which help scientists determine how hot the solar atmosphere is, how strong the sun's magnetic field is and more. RELATED STORIES —Has the sun already passed solar maximum? —NASA's daredevil solar spacecraft survives 2nd close flyby of our sun —Watch eerie 'UFOs' and a solar 'cyclone' take shape in stunning new ESA video of the sun Today's news is only the beginning for the VTF and DKIST. The incredibly complex instrument still requires more testing and set-up, which is expected to be completed by next year. But the newly released first images show great promise for how much we can learn about the sun, our nearest star. These images are "something no other instrument in the telescope can achieve in the same way," said National Solar Observatory optical engineer Stacey Sueoka. "I'm excited to see what's possible as we complete the system."
Channel Post MEA
16-04-2025
- Business
- Channel Post MEA
SandboxAQ Leverages NVIDIA DGX Cloud To Fuel Scientific Discovery
SandboxAQ has announced a collaboration with NVIDIA to accelerate breakthrough innovations across biopharma, chemicals, advanced materials, financial services, cybersecurity, navigation, and medical imaging. SandboxAQ, a member of the NVIDIA Inception program, is leveraging the NVIDIA DGX Cloud AI platform on Google Cloud to build a state-of-the-art Large Quantitative Model (LQM) platform, fueling AI-driven scientific discovery. SandboxAQ is now uniquely positioned to help customers tackle the most complex and consequential business challenges through its LQMs – delivering breakthroughs where traditional models have fallen short – while offering unparalleled speed, scalability, and precision. This collaboration enables SandboxAQ to unlock critical breakthroughs specifically designed to transform customer outcomes, including: Up to 4x Faster Discovery Across Drug, Chemical, and Materials Pipelines: Accelerated by NVIDIA DGX Cloud, SandboxAQ replaces slow, resource-intensive design-make-test cycles with high-performance, equation-based simulations – reducing discovery timelines from months to weeks. Enhanced modeling capabilities support simultaneous optimization across multiple parameters, enabling faster validation of promising candidates and accelerating breakthroughs with greater confidence. Accelerated by NVIDIA DGX Cloud, SandboxAQ replaces slow, resource-intensive design-make-test cycles with high-performance, equation-based simulations – reducing discovery timelines from months to weeks. Enhanced modeling capabilities support simultaneous optimization across multiple parameters, enabling faster validation of promising candidates and accelerating breakthroughs with greater confidence. Breakthrough Datasets, Curated with DGX Cloud: SandboxAQ is generating high-fidelity scientific datasets, combining chemical and biological simulations. These methods leverage equation-based LQM models to reveal interactions between small molecules and complex biological targets that were previously difficult to detect including conformer libraries for generative chemistry and synthetic affinity data for training predictive models. By powering causal knowledge graphs and more accurate molecular design, these datasets reduce false positives and improve success rates across the R&D pipeline. SandboxAQ is generating high-fidelity scientific datasets, combining chemical and biological simulations. These methods leverage equation-based LQM models to reveal interactions between small molecules and complex biological targets that were previously difficult to detect including conformer libraries for generative chemistry and synthetic affinity data for training predictive models. By powering causal knowledge graphs and more accurate molecular design, these datasets reduce false positives and improve success rates across the R&D pipeline. Agentic AI Chemist – A New Era of Autonomous Discovery: SandboxAQ's AI Chemist combines and orchestrates multiple LQMs to transform the scale of the research and development process. It autonomously explores millions of potential chemical pathways, far beyond what a human chemist could evaluate, enabling the discovery of novel molecules and the optimization of compounds for clinical and scale up success. Research Breakthroughs Today's announcement builds on previous collaboration between SandboxAQ and NVIDIA: 2024 Breakthrough : SandboxAQ and NVIDIA achieved an 80x acceleration in quantum chemistry calculations using CUDA-accelerated Density Matrix Renormalization Group (DMRG), enabling accurate simulation of enzyme active sites and complex catalysts previously impossible due to computational limitations. : SandboxAQ and NVIDIA achieved an using CUDA-accelerated Density Matrix Renormalization Group (DMRG), enabling accurate simulation of enzyme active sites and complex catalysts previously impossible due to computational limitations. 2025 Breakthrough : In the newly published joint research paper, 'Orbital Optimization of Large Active Spaces via AI-Accelerators,' for the first time, researchers successfully performed orbital optimization on a system with 82 electrons in 82 orbitals – more than doubling the size of simulations compared to previous works. This groundbreaking advance for GPU accelerated quantum chemistry calculations pushes the capabilities for molecular simulations into a regime that has thus far been entirely out of reach, with potentially far-reaching implications in catalysis, material science and high-dimensional parameter optimization. Transformative Impact Across Key Customer Domains SandboxAQ's enhanced capabilities deliver strategic outcomes across customer innovation and critical workflows: Biopharma and Healthcare : Proven track record of accelerating preclinical pipelines for pharma companies by rapidly generating and optimizing therapeutic candidates based on significantly improved predictability of drug efficacy and safety. : Proven track record of accelerating preclinical pipelines for pharma companies by rapidly generating and optimizing therapeutic candidates based on significantly improved predictability of drug efficacy and safety. Chemicals and Materials : Enabling deeper, faster exploration and validation of sustainable chemical processes to unlock carbon and hydrogen utilization as well as next-generation energy storage technologies. : Enabling deeper, faster exploration and validation of sustainable chemical processes to unlock carbon and hydrogen utilization as well as next-generation energy storage technologies. Cybersecurity and Strategic Infrastructure: Leveraging advanced modeling and predictive capabilities to enhance agility, strengthen resilience, and support proactive cybersecurity postures. Pioneering How Organizations Can Effectively Leverage AI SandboxAQ is pioneering a new category of enterprise AI through its proprietary Large Quantitative Models (LQMs), a platform specifically engineered to solve massively complex, high-stakes problems where precision and deterministic outputs are critical. Unlike generalized frontier models, SandboxAQ's LQMs are designed to reflect the underlying laws of physics, chemistry, biology, and economics – enabling outcomes that are not just predictive, but scientifically reliable. In fields like drug discovery, SandboxAQ trains LQMs on high-fidelity, domain-specific datasets to dramatically improve accuracy, reduce false positives, and accelerate the path from hypothesis to therapeutic insight. This focus on scientifically grounded, application-specific modeling sets SandboxAQ apart, empowering organizations to unlock value in areas where conventional AI simply cannot deliver. 'Our expanded work with NVIDIA accelerates our customers' ability to innovate and lead in their fields,' said Jack Hidary , CEO of SandboxAQ. 'By developing our platform on NVIDIA DGX Cloud and continuing our research collaboration, SandboxAQ will deliver a level of performance and insight that gives our customers a clear edge in accelerating innovation.' 'SandboxAQ is pushing the boundaries of AI-native science,' said Alexis Bjorlin , Vice President of NVIDIA DGX Cloud. 'NVIDIA DGX Cloud provides an AI development platform with essential scale and optimized application performance, empowering SandboxAQ to deliver cutting-edge capabilities and drive real-world impact for organizations tackling society's most critical challenges.' 0 0
Forbes
11-04-2025
- Science
- Forbes
Poetry And Deception: Secrets Of Anthropic's Claude 3.5 Haiku AI Model
Anthropic AI recently published two breakthrough research papers that provide surprising insights into how an AI model 'thinks.' One of the papers follows Anthropic's earlier research that linked human-understandable concepts with LLMs' internal pathways to understand how model outputs are generated. The second paper reveals how Anthropic's Claude 3.5 Haiku model handled simple tasks associated with ten model behaviors. These two research papers have provided valuable information on how AI models work — not by any means a complete understanding, but at least a glimpse. Let's dig into what we can learn from that glimpse, including some possibly minor but still important concerns about AI safety. LLMs such as Claude aren't programmed like traditional computers. Instead, they are trained with massive amounts of data. This process creates AI models that behave like black boxes, which obscures how they can produce insightful information on almost any subject. However, black-box AI isn't an architectural choice; it is simply a result of how this complex and nonlinear technology operates. Complex neural networks within an LLM use billions of interconnected nodes to transform data into useful information. These networks contain vast internal processes with billions of parameters, connections and computational pathways. Each parameter interacts non-linearly with other parameters, creating immense complexities that are almost impossible to understand or unravel. According to Anthropic, 'This means that we don't understand how models do most of the things they do.' Anthropic follows a two-step approach to LLM research. First, it identifies features, which are interpretable building blocks that the model uses in its computations. Second, it describes the internal processes, or circuits, by which features interact to produce model outputs. Because of the model's complexity, Anthropic's new research could illuminate only a fraction of the LLM's inner workings. But what was revealed about these models seemed more like science fiction than real science. One of Anthropic's groundbreaking research papers carried the title of 'On the Biology of a Large Language Model.' The paper examined how the scientists used attribution graphs to internally trace how the Claude 3.5 Haiku language model transformed inputs into outputs. Researchers were surprised by some results. Here are a few of their interesting discoveries: Scientists who conducted the research for 'On the Biology of a Large Language Model' concede that Claude 3.5 Haiku exhibits some concealed operations and goals not evident in its outputs. The attribution graphs revealed a number of hidden issues. These discoveries underscore the complexity of the model's internal behavior and highlight the importance of continued efforts to make models more transparent and aligned with human expectations. It is likely these issues also appear in other similar LLMs. With respect to my red flags noted above, it should be mentioned that Anthropic continually updates its Responsible Scaling Policy, which has been in effect since September 2023. Anthropic has made a commitment not to train or deploy models capable of causing catastrophic harm unless safety and security measures have been implemented that keep risks within acceptable limits. Anthropic has also stated that all of its models meet the ASL Deployment and Security Standards, which provide a baseline level of safe deployment and model security. As LLMs have grown larger and more powerful, deployment has spread to critical applications in areas such as healthcare, finance and defense. The increase in model complexity and wider deployment has also increased pressure to achieve a better understanding of how AI works. It is critical to ensure that AI models produce fair, trustworthy, unbiased and safe outcomes. Research is important for our understanding of LLMs, not only to improve and more fully utilize AI, but also to expose potentially dangerous processes. The Anthropic scientists have examined just a small portion of this model's complexity and hidden capabilities. This research reinforces the need for more study of AI's internal operations and security. In my view, it is unfortunate that our complete understanding of LLMs has taken a back seat to the market's preference for AI's high performance outcomes and usefulness. We need to thoroughly understand how LLMs work to ensure safety guardrails are adequate.
Yahoo
09-03-2025
- Business
- Yahoo
UPA Corporation Berhad (KLSE:UPA) Could Be At Risk Of Shrinking As A Company
When researching a stock for investment, what can tell us that the company is in decline? Businesses in decline often have two underlying trends, firstly, a declining return on capital employed (ROCE) and a declining base of capital employed. Trends like this ultimately mean the business is reducing its investments and also earning less on what it has invested. On that note, looking into UPA Corporation Berhad (KLSE:UPA), we weren't too upbeat about how things were going. For those who don't know, ROCE is a measure of a company's yearly pre-tax profit (its return), relative to the capital employed in the business. The formula for this calculation on UPA Corporation Berhad is: Return on Capital Employed = Earnings Before Interest and Tax (EBIT) ÷ (Total Assets - Current Liabilities) 0.0017 = RM491k ÷ (RM307m - RM24m) (Based on the trailing twelve months to December 2024). So, UPA Corporation Berhad has an ROCE of 0.2%. Ultimately, that's a low return and it under-performs the Forestry industry average of 2.7%. See our latest analysis for UPA Corporation Berhad While the past is not representative of the future, it can be helpful to know how a company has performed historically, which is why we have this chart above. If you want to delve into the historical earnings , check out these free graphs detailing revenue and cash flow performance of UPA Corporation Berhad. In terms of UPA Corporation Berhad's historical ROCE movements, the trend doesn't inspire confidence. To be more specific, the ROCE was 5.0% five years ago, but since then it has dropped noticeably. Meanwhile, capital employed in the business has stayed roughly the flat over the period. Companies that exhibit these attributes tend to not be shrinking, but they can be mature and facing pressure on their margins from competition. If these trends continue, we wouldn't expect UPA Corporation Berhad to turn into a multi-bagger. In summary, it's unfortunate that UPA Corporation Berhad is generating lower returns from the same amount of capital. In spite of that, the stock has delivered a 20% return to shareholders who held over the last five years. Regardless, we don't like the trends as they are and if they persist, we think you might find better investments elsewhere. If you want to know some of the risks facing UPA Corporation Berhad we've found 4 warning signs (2 can't be ignored!) that you should be aware of before investing here. While UPA Corporation Berhad isn't earning the highest return, check out this free list of companies that are earning high returns on equity with solid balance sheets. Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team (at) article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned. Sign in to access your portfolio
