Frightening sight: Dozens of spooky glowing eyes appear from the shadows
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Yahoo
10 hours ago
- Yahoo
The meteor shower trio continues in our night skies
What's better than one meteor shower? Three of them sending streaks of light across the night sky at the same time! Each year, during the month of July, our planet Earth plunges into three separate streams of comet debris, each composed of ice and dust that orbits around the Sun. As we fly through these streams, the atmosphere sweeps up the tiny meteoroids directly in our path, which flash by overhead, producing a spectacular trio of overlapping meteor showers. The first of these, the alpha Capricornids, originates from a comet known as 169P/NEAT. Although the meteor shower has been observed for a very long time, its parent body was not discovered until 2005. Originally thought to be an asteroid, further observations revealed weak comet activity when it neared the Sun. We begin to see meteors from the alpha Capricornids in early July each year, radiating out from the constellation Capricornus, in the southern sky. This shower often goes unmentioned and unnoticed, though, as it produces just a handful of meteors each night from early July through mid-August. The radiant of the alpha Capricornids, on the night of the meteor shower's peak, on July 31-August 1. The First Quarter Moon will be in the western sky, setting around midnight. (Scott Sutherland/Stellarium/NASA's Goddard Scientific Visualization Studio) However, despite their rarity, alpha Capricornids tend to be fairly bright, and can even include a few fireballs — exceptionally bright meteors that are easily visible for hundreds of kilometres around on clear nights, even for observers trapped under heavily light-polluted skies. The Perseids are the second of this trio to start. Originating from a comet called 109P/Swift–Tuttle, due to the angle of the meteoroids as they enter the atmosphere, the meteors appear from the direction of the constellation Perseus, in the northern sky. The radiant of the Perseids (the point in the sky the shower appears to originate from) is located in the northeastern sky each night from mid-July through late August. The view in this simulation depicts the night of the peak, on August 12-13, 2025. The phase of the Moon (Waning Gibbous) is shown in the top right corner. (Simulation courtesy Stellarium. Moon phase from NASA's Goddard Scientific Visualization Studio) The third is the Southern delta Aquariids. Although we don't know for sure, this shower appears to come from an oddball comet called 96P/Machholz. The odd thing about this object is that it's apparently unlike any other comet in our solar system, with a unique orbit and chemical composition. It's even possible that it's an alien comet that was long ago captured by our Sun's gravity as it wandered through interstellar space. The meteors from Comet Machholz's debris stream can be traced back to the constellation Aquarius, in the southern sky. Also, due to the specific angle of the comet's path through the solar system, it produces a slightly better show in the southern hemisphere than the north. However, here in Canada, we can still see a decent number of meteors from it, if we know when to look. The radiant of the delta Aquariids is located in the southern sky each night from mid-July through early August. The view in this simulation depicts the night of the peak, on July 30, 2025, although the delta Aquariids peak between the 29th and 31st. The July 30 phase of the Moon (Waxing Crescent) is shown in the top right corner. (Simulation courtesy Stellarium. Moon phase from NASA's Goddard Scientific Visualization Studio) READ MORE: All three of these meteors showers began slowly, producing just a few meteors at their start — the alpha Capricornids in early July, and the Perseids and delta Aquariids around the middle of the month. The end of July was the best time to view the trio. Based on their typical behaviour, by the last few nights of the month, around 20 Perseid meteors per hour would have been streaking out of the northeast, crisscrossing with about 20 delta Aquariids per hour from the southeast. On the night of the 31st, the alpha Capricornids would have added up to 5 more per hour to the overlapping display. With the timing of the Moon's phases, the nights of the 29th, 30th, and 31st were the best time to go out and spot these meteors. This is because the Moon was off in the west throughout the evening and set by midnight. That left the rest of the night with a dark sky for picking out those brief flashes of light overhead. This wider simulation of the eastern sky, on the night of July 31-August 1, 2025, shows the radiants of the Perseid, delta Aquariid, and alpha Capricornid meteor showers in their respective spots. The First Quarter Moon is setting on the western horizon at this time, out of view of the observer. (Scott Sutherland/Stellarium) DON'T MISS: August Update Now that we're into August, the number of Perseid meteors will continue to rise up until the night of the 12th. At the same time, the number of delta Aquariids and alpha Capricornids will ramp down significantly. Thus, total meteor numbers will remain fairly constant over the next week or so, but will more heavily favour the Perseids out of the northeast. There's one caveat to this, though. During the first two weeks of August, the Moon will be casting off quite a bit of light as it passes through its brightest phases — Waxing Gibbous from the 2nd to the 7th, the Full Sturgeon Moon on the 8th-9th, and Waning Gibbous from the 9th to the 14th. The phases of the Moon from July 27 through August 16 reveal why sky conditions may be best for this meteor shower trio at the end of July. (Scott Sutherland/NASA's Goddard Scientific Visualization Studio) Having a dark sky is important for meteor watching, for two reasons: our eyes need to fully adapt to the dark to become sensitive enough to pick up the faintest flashes of light, and the contrast of the mostly-black background of space helps us in spotting the brief meteor streaks. Bright moonlight acts in exactly the same way as urban light pollution, especially on humid summer nights, when the added water vapour in the air easily refracts that moonlight into our eyes. The sky becomes 'washed out', with only the brighest stars remaining visible, and similarly only the brighest meteors tend to be able to pierce that 'veil' of light. Normally, as the Perseids reach their peak on the night of the 12th, observers under clear dark skies have a chance to spot up to 75-100 meteors every hour. This year, we will likely see closer to 40-50 per hour. Weather conditions could reduce that even further. Fortunately, the Perseids are well-known for producing the greatest number of fireballs! Watch below: Perseid fireball captured by NASA all-sky camera Click here to view the video After the peak of the Perseids, we can still spot meteors from the shower as it ramps down, right up until August 24. So, watch for clear skies in your forecast and keep an eye out for meteors and fireballs flashing through the night. (Editor's note: This article has gone through a significant update to include additional information regarding the alpha Capricornids meteor shower and how it will add to the show produced by the Perseids and delta Aquariids.) Thumbnail image produced using the open-source planetarium software, Stellarium. Watch below: What do we know about Interstellar Comet 3I/ATLAS? Click here to view the video Solve the daily Crossword
Forbes
21 hours ago
- Forbes
AI Training Gets 10x Faster, 95% Cheaper With Decentralized Strategy
A quiet shift in the foundations of artificial intelligence (AI) may be underway, and it is not happening in a hyperscale data center. 0G Labs, the first decentralized AI protocol (AIP), in collaboration with China Mobile, recently announced a technical breakthrough that could have sweeping implications for how businesses access and deploy large language models. Their innovation is a new method of training massive AI models with over 100 billion parameters, without needing the ultra-high-speed internet or expensive centralized infrastructure typically required. At first glance, this might sound like a win for the engineering world. But the real story is economic and strategic. What 0G Labs has achieved could lower the cost of building AI, put more control back into the hands of enterprises, and open the door for new players to enter the space. What It Means For AI Training To understand the shift, it helps to revisit how large-scale AI models are currently trained. Models like OpenAI's GPT-4 or Anthropic's Claude require vast computing power and network throughput. Traditionally, this means training them on powerful GPUs connected across high-speed, centralized data centers owned or rented from companies like Amazon Web Services, Google Cloud, or Microsoft Azure. As of early 2025, OpenAI's leadership, including Sam Altman, publicly stated that training GPT‑4 cost over $100 million. This is supported both by official statements and multiple cost models in recent AI analysis reportsIt is a model that demands capital, talent, and infrastructure that few organizations can afford. 0G Labs Is Challenging That Assumption For AI Training Their newly published framework, called DiLoCoX, introduces a low-communication training method that dramatically reduces the need for high-bandwidth connectivity. In practical terms, they successfully trained a 107 billion parameter model on a 1 Gbps network using decentralized clusters. This record is a 10x improvement of the previous record and the 300x speed-up breakthrough that made this possible for the first time. This is roughly the bandwidth of a typical office internet connection. Instead of building everything in one giant compute center, their approach links together smaller, distributed machines and optimizes how information is shared between them. The result is a highly scalable, cost-efficient way to train massive models outside the traditional cloud. In speaking with 0G labs founder and CEO Michael Heinrich, he said 'DiLoCoX marks a pivotal step in democratizing LLM training: bridging the gap between massive foundation models and decentralized clusters connected by slow, unreliable networks. By combining pipeline parallelism, delay‑tolerant communication overlap, and adaptive gradient compression, the framework delivers scale and speed previously thought exclusive to high‑bandwidth data centers. This will usher in a new era where large‑scale AI training is no longer tethered to centralized infrastructure.' Why Does AI Training Matter for Business At a time when every enterprise is under pressure to do more with AI, infrastructure is quickly becoming the bottleneck. Some businesses are starting to look at decentralized AI by design. Building large models remains expensive, exclusive, and largely confined to companies with deep resources or strategic cloud partnerships. 0G's breakthrough opens up a third path. This is not just a story of cost savings. It is a story of optionality and control. 1. Lowering the Barrier to Entry DiLoCoX's approach reduces the infrastructure by up to 95% required to participate in the LLM race. For startups, this means the ability to experiment and scale without burning through venture capital on GPU spend. For mid-sized enterprises, it offers the possibility of training models in-house without making large cloud commitments. For governments and research labs, it means more accessible and sovereign development of AI capabilities. 2. Strategic Independence from Hyperscalers Most AI training today depends on three cloud providers. That concentration carries risk in terms of cost escalation, vendor lock-in, and compliance. If your business depends on AI but also operates in a sensitive sector like healthcare, defense, or finance, the ability to train or fine-tune models independently becomes a powerful strategic lever. Decentralized AI offers a route toward digital autonomy. By breaking the assumption that cutting-edge AI must be trained inside centralized cloud platforms, 0G's model creates new room for competition and for innovation. 3. Aligning with Data Privacy and Compliance Needs Many companies are cautious about uploading proprietary data to cloud-based models or training environments. With decentralized training, it becomes possible to keep data local within jurisdiction, within the firewall, or even on edge devices while still participating in large-scale AI development. This is particularly attractive in regions with strict data sovereignty laws such as the European Union or countries building their own AI ecosystems. The 0G network never sees any of the private data 4. Accelerating Innovation in Underserved Markets The high cost of entry has kept many countries and industries on the sidelines of advanced AI development. DiLoCoX lowers that threshold. A university in Kenya, a telecom provider in Southeast Asia, or a regional bank in Latin America may not have access to the same compute as Silicon Valley, but they may soon have the tools to train and deploy their intelligent systems on existing infrastructure. 5. Geopolitical and Regulatory Risks While the technical achievement is impressive, the involvement of China Mobile raises questions. As tensions between the United States and China continue to escalate over technology leadership and national security, businesses must weigh the potential regulatory scrutiny, data governance concerns, and reputational risks associated with partnerships involving Chinese state-affiliated entities. For companies based in the United States or operating in allied markets, any integration of infrastructure or research tied to China could face export controls, legal restrictions, or public backlash. Organizations exploring decentralized AI solutions will need to consider not just performance and cost, but also political alignment, compliance frameworks, and long-term viability. However, having DiLoCoX on a decentralized infrastructure where the network is trustless, this is not a concern because China Mobile never sees your data, and the system doesn't rely on them for results. Reframing the Business Model of AI If DiLoCoX is widely adopted, it could create ripple effects across the broader AI ecosystem. Cloud revenue models, currently boosted by AI workloads, could face new pricing pressure. AI-as-a-service platforms may need to re-architect to support hybrid or decentralized deployments. Open-source frameworks might grow in influence as decentralization emphasizes interoperability and local control. Enterprise software vendors may need to rethink their AI strategies to reflect a more distributed compute landscape. This shift also aligns with the broader trend of AI for everyone. From low-code agent builders to edge-based inferencing, the movement is toward more accessible, modular, and customizable AI stacks. Decentralized training is the natural extension of that philosophy. An AI Signal for CIOs and CTOs For enterprise leaders, 0G's work serves as a signal not of immediate disruption, but of near-future opportunity. AI is evolving from its critical beginning. Now is the time to reevaluate infrastructure strategy. Should your organization continue investing in cloud-based model hosting, or begin exploring decentralized alternatives? Could your internal data center serve as a node in a distributed training system? Decentralized federated learning is a great way of tapping into private data from different parties on a network, like hospitals training a cancer diagnostic model. Might you partner with others in your sector to co-develop models using decentralized protocols? Even if the answer is not yes today, the emergence of frameworks like DiLoCoX should push AI infrastructure planning higher on the strategic agenda. Businesses that prepare for this shift by building internal capacity, evaluating partners, and understanding the technical stack will be best positioned to move when the economics tip in their favor. A Future Where AI is Built Differently What 0G Labs and China Mobile have demonstrated is more than just a technical proof of concept. It is a new way of thinking about how intelligence is built, trained, and distributed. By showing that it is possible to train 100 billion parameter models without centralized supercomputers, they are not just pushing the boundaries of scale. They are expanding access. For business, that means AI may soon be less about who owns the biggest data center and more about who can build the smartest systems with the most flexibility. That is an AI future worth preparing for.
Medscape
a day ago
- Medscape
Is Your Practice Missing the Next Gastric Cancer Surge?
A study published in Nature Medicine estimated that Helicobacter pylori infection could lead to 11.8 million cases of gastric cancer over the lifetime of today's children if current prevention strategies remain unchanged. The International Agency for Research on Cancer, World Health Organization, analyzed global cancer incidence data 2022 and United Nations demographic information to estimate future mortality. The study focused on people born between 2008 and 2017 to estimate their lifetime cancer risk linked to chronic H pylori infection. According to the study, gastric cancer is the fifth leading cause of cancer death worldwide. Two thirds of future cases are projected in Asia (10.6 million), followed by the Americas (2.0 million), Africa (1.7 million), and Europe (1.2 million), with 900,000 in Europe linked to H pylori . Researchers emphasized that gastric cancer is largely preventable and called for stronger global prevention strategies, including the development of a vaccine against H pylori. Speaking with Univadis Spain , Javier P. Gisbert, MD, PhD, highlighted the urgent need to address H pylori infection. He is the head of the Inflammatory Bowel Disease Unit at Hospital Universitario de La Princesa in Madrid, Spain, associate professor of medicine at Universidad Autónoma de Madrid, and affiliated researcher with the Instituto de Investigación Sanitaria Princesa, Madrid. 'Gastric cancer is a major global health concern, ranking as the fifth most common cancer worldwide. The main cause is H pylori infection. If we could eradicate this bacterium, we would eliminate at least 90% of the gastric tumors it causes. In Spain alone, approximately 60,000 new cases of gastric cancer are expected in this birth cohort, with approximately 40,000 linked to H pylori infection. These figures show that this bacterium, and efforts to diagnose and prevent it, must be taken very seriously,' he said. Preventive Measures In 2021, the European Union launched the Beating Cancer Plan, followed by European Council recommendations that highlight population-based screening and treatment of H pylori as key tools to prevent gastric cancer. According to Gisbert, H pylori is usually acquired in early childhood, but the cancer it can cause typically appears decades later, often after the age of 50 or 60 years. 'Chronic H pylori infection gradually damages the stomach lining,' he explained. 'It starts with superficial gastritis, progresses to atrophic gastritis, then intestinal metaplasia, and finally dysplasia the last stage before cancer. If we treat the infection early, before these changes occur, we can prevent gastric cancer.' Despite this risk, the incidence of gastric cancer in Spain remains relatively low, under 10 cases per 100,000 people per year. For this reason, screening asymptomatic people for H pylori is not considered necessary nationwide. 'In countries with higher gastric cancer rates, H pylori screening would be cost-effective,' Gisbert said. 'But in Spain, it's not clearly justified.' Practice Gaps Gisbert is also a researcher at the Biomedical Research Network Centre for Liver and Digestive Diseases. He also serves as principal investigator of the European H pylori Registry, a multinational initiative tracking real-world management of the infection. He recently led a study assessing how Spanish gastroenterologists outside the registry manage H pylori infections. The results, published in Helicobacter , revealed the following gaps in clinical practice: '17% of specialists did not test for H pylori in patients with gastrointestinal bleeding from peptic ulcers, and 35% did not start treatment at the time of diagnosis in these cases. Only 25% were aware of local clarithromycin resistance rates, and only 37% regularly assessed the effectiveness of eradication treatments. Additionally, 74% of the specialists did not confirm penicillin allergy before prescribing the treatment. Moreover, 32% did not investigate first-degree relatives of patients with gastric cancer,' summarized Gisbert. Conclusion 'Given that gastric cancer is largely preventable, more active intervention and control programs should be implemented in these high-resource East Asian countries. This indicates that, as in human papillomavirus vaccine programs for cervical cancer prevention or hepatitis B vaccine programs to reduce the risk of liver cancer, an H pylori vaccine would greatly advance the fight against gastric cancer, given that vaccination is one of the most context-responsive prevention strategies and is highly adaptable, especially in low- and middle-income settings where we expect to see a high number of H pylori -attributable gastric cancer cases,' the authors concluded. Gisbert reported having no conflicts of interest.
