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3D Energi Runs Out of Cash for Victoria Drill Campaign, Suspends Trading

3D Energi Ltd said Tuesday it has voluntarily halted trading on the Australian Securities Exchange (ASX), having defaulted on the payment of its share of costs in a ConocoPhillips-led exploration campaign in the Otway basin offshore Victoria. “Joint venture cash calls for the drilling program are higher than originally forecast and a balance of approximately […]

3D Energi Ltd said Tuesday it has voluntarily halted trading on the Australian Securities Exchange (ASX), having defaulted on the payment of its share of costs in a ConocoPhillips-led exploration campaign in the Otway basin offshore Victoria.

“Joint venture cash calls for the drilling program are higher than originally forecast and a balance of approximately $2.5 million remains outstanding by the company which it does not currently have”, Melbourne-based 3D Energi said in a stock filing.

“A default notice has been issued by the joint venture operator to the company with a remedy period to 6th February.

“Additional forecast company drilling program expenditure subject to cash calls due on 6th February is currently estimated at approximately $5.3 million, which if not paid by that date may well become the subject of an additional default notice and remedy period.

“Consequently, the company is implementing a suspension of the trading of its shares on ASX while it addresses its funding position and the implications of payment default on the level of its ongoing interest in the permit”.

3D Energi plans to resume ASX trading in the first week of February.

Earlier this month it announced the Charlemont-1 gas discovery, the joint venture’s second discovery under the VIC/P79 exploration after Essington-1. The newest well targeted the penultimate prospect in the Charlemont trend, which culminates with the La Bella discovery, according to 3D Energi.

“Phase 1 of the Otway Exploration Drilling Program has identified important new natural gas resources close to existing offshore gas production and processing infrastructure in the Otway basin, supplying the Australian domestic gas market”, 3D Energi executive chair Noel Newell said in a statement January 14 announcing the second discovery. “This enhances the strategic significance of the discovery and supports future development optionality, subject to further technical and commercial evaluation, consistent with the company’s objective of contributing new gas supply to a tightening East Coast market”.

Explaining the higher-than-expected costs, 3D Energi said Tuesday, “In the case of the Essington-1 well, the cost variance primarily reflects the decision to undertake an extensive wireline logging and Ora formation testing program following confirmation of a significant gas discovery in the Waarre A reservoir. These activities were undertaken based on success to appropriately assess the discovery and materially enhance technical understanding of the reservoir for commercial assessment”.

“For Charlemont-1, material incremental costs arose from a combination of weather-related delays during mobilization and the encounter of overpressured gas while drilling”, it added. “These conditions necessitated a revised well design, additional casing, sourcing of supplementary equipment, regulatory approval from NOPSEMA (National Offshore Petroleum Safety, and Environment Management Authority) and the execution of a more complex evaluation program. As a result, the Charlemont-1 well duration extended by approximately 14 days beyond the original planned schedule, which directly resulted in additional rig time and associated operational costs”.

The Transocean Equinox drilling rig has been transferred to another operator in the Otway region, 3D Energi said.

3D Energi owns 20 percent in the VIC/P79 exploration permit. ConocoPhillips is operator with a 51 percent stake. Korea National Oil Co owns 29 percent.

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3D Energi Runs Out of Cash for Victoria Drill Campaign, Suspends Trading

3D Energi Ltd said Tuesday it has voluntarily halted trading on the Australian Securities Exchange (ASX), having defaulted on the payment of its share of costs in a ConocoPhillips-led exploration campaign in the Otway basin offshore Victoria. “Joint venture cash calls for the drilling program are higher than originally forecast and a balance of approximately $2.5 million remains outstanding by the company which it does not currently have”, Melbourne-based 3D Energi said in a stock filing. “A default notice has been issued by the joint venture operator to the company with a remedy period to 6th February. “Additional forecast company drilling program expenditure subject to cash calls due on 6th February is currently estimated at approximately $5.3 million, which if not paid by that date may well become the subject of an additional default notice and remedy period. “Consequently, the company is implementing a suspension of the trading of its shares on ASX while it addresses its funding position and the implications of payment default on the level of its ongoing interest in the permit”. 3D Energi plans to resume ASX trading in the first week of February. Earlier this month it announced the Charlemont-1 gas discovery, the joint venture’s second discovery under the VIC/P79 exploration after Essington-1. The newest well targeted the penultimate prospect in the Charlemont trend, which culminates with the La Bella discovery, according to 3D Energi. “Phase 1 of the Otway Exploration Drilling Program has identified important new natural gas resources close to existing offshore gas production and processing infrastructure in the Otway basin, supplying the Australian domestic gas market”, 3D Energi executive chair Noel Newell said in a statement January 14 announcing the second discovery. “This enhances the strategic significance of the discovery and supports future development optionality, subject to further technical and commercial evaluation,

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Gauging the real impact of AI agents

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Photonic chip vendor snags Gates investment

“Moore’s Law is slowing, but AI can’t afford to wait. Our breakthrough in photonics unlocks an entirely new dimension of scaling, by packing massive optical parallelism on a single chip,” said Patrick Bowen, CEO of Neurophos. “This physics-level shift means both efficiency and raw speed improve as we scale up, breaking free from the power walls that constrain traditional GPUs.” The new funding includes investments from Microsoft’s investment fund M12 that will help speed up delivery of Neurophos’ first integrated photonic compute system, including datacenter-ready OPU modules. Neurophos is not the only company exploring this field. Last April, Lightmatter announced the launch of photonic chips to tackle data center bottlenecks, And in 2024, IBM said its researchers were exploring optical chips and developing a prototype in this area.

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Intel wrestling with CPU supply shortage

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Intel’s AI pivot could make lower-end PCs scarce in 2026

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Reports of SATA’s demise are overblown, but the technology is aging fast

The SATA 1.0 interface made its debut in 2003. It was developed by a consortium consisting of Intel, Dell, and storage vendors like Seagate and Maxtor. It quickly advanced to SATA III in 2009, but there never was a SATA IV. There was just nibbling around the edges with incremental updates as momentum and emphasis shifted to PCI Express and NVMe. So is there any life to be had in the venerable SATA interface? Surprisingly, yes, say the analysts. “At a high level, yes, SATA for consumer is pretty much a dead end, although if you’re storing TB of photos and videos, it is still the least expensive option,” said Bob O’Donnell, president and chief analyst with TECHnalysis Research. Similarly for enterprise, for massive storage demands, the 20 and 30 TB SATA drives from companies like Seagate and WD are apparently still in wide use in cloud data centers for things like cold storage. “In fact, both of those companies are seeing recording revenues based, in part, on the demand for these huge, high-capacity low-cost drives,” he said. “SATA doesn’t make much sense anymore. It underperforms NVMe significantly,” said Rob Enderle, principal analyst with The Enderle Group. “It really doesn’t make much sense to continue make it given Samsung allegedly makes three to four times more margin on NVMe.” And like O’Donnell, Enderle sees continued life for SATA-based high-capacity hard drives. “There will likely be legacy makers doing SATA for some time. IT doesn’t flip technology quickly and SATA drives do wear out, so there will likely be those producing legacy SATA products for some time,” he said.

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DCN becoming the new WAN for AI-era applications

“DCN is increasingly treated as an end-to-end operating model that standardizes connectivity, security policy enforcement, and telemetry across users, the middle mile, and cloud/application edges,” Sanchez said. Dell’Oro defines DCN as platforms and services that deliver consistent connectivity, policy enforcement, and telemetry from users, across the WAN, to distributed cloud and application edges spanning branch sites, data centers and public clouds. The category is gaining relevance as hybrid architectures and AI-era traffic patterns increase the operational penalty for fragmented control planes. DCN buyers are moving beyond isolated upgrades and are prioritizing architectures that reduce operational seams across connectivity, security and telemetry so that incident response and change control can follow a single thread, according to Dell’Oro’s research. What makes DCN distinct is that it links user-to-application experience with where policy and visibility are enforced. This matters as application delivery paths become more dynamic and workloads shift between on-premises data centers, public cloud, and edge locations. The architectural requirement is eliminating handoffs between networking and security teams rather than optimizing individual network segments. Where DCN is growing the fastest Cloud/application edge is the fastest-growing DCN pillar. This segment deploys policy enforcement and telemetry collection points adjacent to workloads rather than backhauling traffic to centralized security stacks. “Multi-cloud remains a reality, but it is no longer the durable driver by itself,” Sanchez said. “Cloud/application edge is accelerating because enterprises are trying to make application paths predictable and secure across hybrid environments, and that requires pushing application-aware steering, policy enforcement, and unified telemetry closer to workloads.”

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Microsoft will invest $80B in AI data centers in fiscal 2025

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John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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