Applied Computing wants to give oil and gas operators an AI model for the entire plant

techcrunch.com Jul 16, 2026

Applied Computing wants to give oil and gas operators an AI model for the entire plant

Curated by Shubham · TechCapsules · Jul 16, 2026

AI-summarised brief · reviewed before publication

Applied Computing, a London-based startup, has secured a $20 million Series A led by KBR and Databricks Ventures to develop Orbital, an AI model for oil, gas, and petrochemical facilities. The model combines sensor data, physics-based modeling, and language processing to enable real-time analysis and predictive simulations. The startup claims Orbital can drastically reduce investigation times for anomalies, helping operators optimize energy use and output. Applied Computing reports double-digit millions in annual recurring revenue and has clients among major upstream and downstream energy companies.

💡 Why It Matters

· Applied Computing’s AI model addresses a critical inefficiency in energy operations—underutilized data—by integrating real-time sensor inputs with physics and engineering knowledge.
· This approach could redefine how energy firms make operational decisions, offering a competitive edge in an industry where even minor improvements in efficiency translate to significant cost savings.

AI Capsules Energy Funding

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Japan Calls for ‘Level Playing Field’ to Protect Thailand’s Automotive Hub in…

Japanese Ambassador Masato Otaka used the opening of the Nikkei Asia Forum APAC 2026 in Bangkok to urge a “level playing field” for the automotive sector, warning that artificial‑intelligence‑driven disruptions threaten Thailand’s role as a regional car‑export hub, especially for pickup trucks. He highlighted the long‑standing Japan‑Thailand manufacturing partnership and stressed that preserving equitable competition is essential for continued growth. Otaka then shifted to energy security, noting that recent South‑China‑Sea tensions have exposed Asia’s vulnerability: Japan imports over 90 % of its oil from the Middle East, while Thailand sources about half of its oil and LNG from the same region. He warned that volatile fuel prices could hit manufacturers, SMEs and households, underscoring the need for coordinated energy frameworks.

💡 Without safeguards, AI‑driven shifts could erode Thailand’s automotive export base, jeopardising a key pillar of Japan‑Thailand economic ties. Energy volatility compounds the risk, making coordinated stability measures vital for regional manufacturing resilience.

mauinews.com · Jul 16

Gov. Green signs bills targeting ‘deepfakes’

Governor Josh Green of Hawaii signed two bills aimed at regulating artificial‑intelligence applications. The first creates consumer‑protection standards for “deepfake” technology that can mimic a person’s voice, face or likeness, defining harmful uses and granting victims civil remedies, including injunctive relief, punitive damages and up to $25,000 per offending piece of content. The legislation expands on federal statutes by clarifying malicious deepfake scenarios and allowing private lawsuits. The second bill addresses generative conversational AI, especially for minors, mandating operator disclosures, protocols for suicide‑related prompts, and annual reporting to the state’s Behavioral Health Administration. It also seeks to curb addictive design patterns and prevent chatbots from being presented as human. Both measures aim to balance AI innovation with safeguards against misuse.

💡 By giving victims a clear path to sue for deepfake harms, Hawaii sets a precedent for state‑level accountability that could reshape how AI content is policed nationwide.

fedscoop.com · Jul 16

Despite revisions, GSA’s proposed AI acquisition rule still falls short, stakeholders say

Stakeholders at a Tuesday listening session warned that the General Services Administration’s revised AI acquisition rule contains language and contractual terms. Palantir’s U.S. government legal head Menaka Kalaskar argued the rule could force agencies to seek non‑GSA contracts for large‑language‑model services because the proposed notice‑of‑material‑change deadlines and license provisions clash with commercial practice and the Federal Acquisition Streamlining Act. The rule, first issued in January and updated in June, expands definitions and scope but retains clauses on “unbiased AI principles” and government ownership of metadata, which critics say are vague. Professor Jessica Tillman noted the rule’s intent to bar AI vendors from training on government data, yet loopholes remain, leaving agencies vulnerable to indirect data exploitation. Comment runs until Aug. 3.

💡 Agencies may be forced onto alternative procurement paths, fragmenting government AI adoption and raising compliance costs.

interestingengineering.com · Jul 16

Elon Musk acquires firm that operates mobile gas, diesel turbines; set to…

Elon Musk has reportedly acquired APR Energy, a provider of rapidly deployable mobile power generation systems, to support the expanding electricity demands of his artificial intelligence venture, xAI. The deal, revealed through regulatory filings rather than an official announcement, grants xAI access to APR’s fleet of gas turbine and reciprocating engine systems capable of generating over one gigawatt of electricity. These modular units offer a strategic advantage by allowing quick installation, bypassing the lengthy construction timelines associated with traditional permanent grid infrastructure. This acquisition addresses the critical challenge of securing reliable power for large-scale AI data centers. However, the move has sparked environmental concerns, as APR Energy’s portfolio relies primarily on natural gas and diesel. Critics note that these turbines could emit significant nitrogen oxides, exacerbating pollution in nearby communities like Boxtown, where cancer risks are already elevated. The transaction underscores the growing tension between the immediate energy requirements of advanced computing operations and the environmental impact of fossil fuel-dependent power solutions.

💡 The acquisition prioritizes rapid computational scaling over environmental sustainability, intensifying the conflict between AI expansion and local public health. By bypassing grid constraints with fossil-fuel generators, xAI sets a precedent for tech giants to externalize pollution costs onto vulnerable communities.

infosecurity-magazine.com · Jul 16

Fake Gemini and Claude Code Sites Spread Infostealers Through SEO Poisoning

Security researchers at EclecticIQ identified a malicious campaign deploying fake websites impersonating Google Gemini and Anthropic’s Claude Code to distribute information-stealing malware. Initially flagged by researcher @g0njxa on April 21, the campaign began in early March 2026, targeting users in the US and UK via tailored domains. Attackers used SEO poisoning to rank these fraudulent sites above legitimate results. The malware executes in memory via PowerShell on Windows endpoints, harvesting credentials from browsers, collaboration tools like Slack and Teams, and cloud storage services. It exfiltrates encrypted data to command-and-control servers, granting attackers authenticated access to corporate workspaces, internal communications, and sensitive files. The operation specifically exploits developer trust in AI coding assistants, leveraging their installation processes to compromise enterprise environments and remote access configurations.

💡 This campaign exploits the rapid adoption of AI coding assistants, turning trusted developer tools into high-value entry points for corporate espionage. By targeting specific enterprise communication platforms, attackers bypass traditional perimeter defenses to access sensitive internal data directly.

securitybrief.in · Jul 16

AI reshapes work, safety & sales across Asia Pacific

Technology and channel leaders utilized AI Appreciation Day 2026 to discuss how artificial intelligence is fundamentally altering work dynamics, safety protocols, and sales strategies across the Asia Pacific region. Ling Lu, Head of New Product Development at Jabra, highlighted a significant transition from keyboard-centric interactions to voice-driven workflows in knowledge work. She predicted that voice interaction with AI will achieve mainstream adoption by 2028, becoming as natural as typing. However, this shift introduces critical challenges regarding audio quality, with 99% of knowledge workers reporting that poor audio negatively impacts online meetings. Lu emphasized that AI effectiveness depends on accurate voice capture, making smarter audio technology essential. Innovations in noise reduction and voice isolation are becoming foundational for conversational AI. Businesses must prioritize clear audio infrastructure to unlock full AI value, ensuring that generative tools can accurately process spoken input. This focus on audio quality addresses longstanding hybrid work frustrations while enabling more autonomous and intuitive AI collaboration in professional environments across the region.

💡 The pivot to voice-first AI exposes a critical infrastructure gap where audio quality, not just model intelligence, dictates productivity. Companies ignoring acoustic optimization risk deploying ineffective AI tools that fail to capture user intent accurately.