AI race weakens climate pledges at Google, Amazon

economictimes.indiatimes.com Jul 3, 2026

AI race weakens climate pledges at Google, Amazon

Curated by Shubham · TechCapsules · Jul 3, 2026

AI-summarised brief · reviewed before publication

Google and Amazon reported sharp increases in greenhouse gas emissions, driven by the construction of artificial intelligence infrastructure. Google's total emissions jumped 82 percent since 2019, and 18 percent last year, while Amazon's emissions rose 58 percent over the same period, and 16 percent last year. Both companies have pledged to reach carbon neutrality, with Google aiming to cut emissions in half by 2030 and Amazon by 2040. However, their emissions are rising faster than their sales, with both companies now polluting more for every dollar generated in revenue, posing a challenge to their environmental ambitions.

💡 Why It Matters

· The emissions surge undermines the tech giants' ability to lead by example in reducing carbon footprint.
· Corporate pursuit of profits is outpacing environmental commitments.

Read full article on economictimes.indiatimes.com

Siri AI is finally good, and Apple is going to win the…

Apple's Siri AI is showing promise, despite initial beta issues, and is expected to dominate the AI market due to the company's user-centric approach. The beta tests have yielded varying experiences among AppleInsider testers, with some finding Siri AI to be irritating and no better than its predecessor, while others have had more positive interactions. However, all testers have found exceptional capabilities in Siri AI that surpass its rivals. The issues are expected to be resolved before the public release. Apple's focus on user needs and use cases may give it an edge over competitors. The company's late entry into the AI market may not hinder its success.

💡 Apple's ability to balance technical capabilities with user needs could give it a unique advantage in the AI market. By prioritizing user experience, Apple may be able to create more intuitive and effective AI interactions.

thequantuminsider.com · Jul 3

Researchers Propose Thermodynamic Computing Architecture That Could Dramatically Reduce AI Energy Use

Researchers have proposed a thermodynamic computing architecture that could match GPU-based performance while consuming about 10,000 times less energy. The system uses probabilistic hardware, Boltzmann machines, and denoising models to generate outputs by turning random noise into structured data. The results are based on simulations and a tested random-number circuit, with scaling to larger AI workloads still unresolved. The proposed architecture draws on ideas from statistical mechanics and could perform certain AI tasks with a fraction of the energy required by today's hardware. The study was led by researchers from Extropic Corp. and the Massachusetts Institute of Technology.

💡 Dramatically reducing AI energy use could alleviate the strain on the world's energy infrastructure, as large-scale AI systems are projected to consume a significant portion of global energy production by 2030. Energy-efficient computing architectures can enable fundamentally different approaches to machine learning.

bitcoinworld.co.in · Jul 3

Loqua Launches Beta for Sui-Based Privacy Messenger with zkLogin and AI Agents

Loqua, a privacy-focused messenger on the Sui blockchain, is launching its beta service, combining decentralized and privacy-enhancing features like zkLogin and end-to-end encrypted messaging. The platform aims to provide a unified user experience prioritizing privacy and decentralization. Key features include on-chain chat, token transfers, group chat, and AI agents for interacting with decentralized applications. The beta is open for early access, with users able to sign up using zkLogin and participate in a global chat to earn points for priority testing. The launch represents a growing trend in cryptocurrency, addressing user concerns about privacy and data ownership.

💡 Loqua's integration with Sui's zkLogin and AI agents offers a unique on-chain experience, differentiating it from other privacy-focused messengers. The platform's success could drive further adoption of the Sui blockchain, showcasing its capabilities beyond DeFi and NFTs.

artificialintelligence-news.com · Jul 3

Takeda signs US$600M AI drug discovery deal with Insilico

Takeda has entered a strategic collaboration with Insilico Medicine to use AI in early-stage drug discovery. The agreement gives Takeda access to Insilico's Pharma.AI platform, which supports target identification, molecular design, and clinical trial prediction. Insilico will lead AI-driven discovery work, while Takeda will advance selected candidates through clinical development. The deal includes $60 million in project initiation fees and milestones, with a potential total value of $600 million if milestones are achieved. Takeda will receive exclusive worldwide rights to develop and commercialize novel therapeutics. Insilico is also eligible for tiered royalties on future sales, supporting early-stage research and development.

💡 The deal accelerates Takeda's integration of AI in drug discovery, combining its disease biology expertise with Insilico's AI capabilities. It also underscores Insilico's growing influence in AI-powered drug discovery, with collaborations now valued at over $7 billion.

industrywired.com · Jul 3

Why Every Indian Startup Is Suddenly Becoming an AI Company

Indian startups are rebranding as AI companies to attract investor funding, with many adding "AI-powered" to their descriptions. Despite a broader funding slowdown, AI startups raised close to $500 million in 2025. The India AI Impact Summit in February triggered over $200 billion in investment commitments, with Adani and Microsoft pledging significant amounts. However, most of these companies are not building new AI technology, but rather using existing models and applying them to their products. Only 536 of the 1,920 AI-tagged companies in India have raised institutional funding, with 72% operating at the application layer.

💡 The rush to rebrand as AI companies reveals a funding landscape where investors prioritize one sector over others. Founders are responding to clear signals from investors, adjusting their pitch decks to secure funding in a competitive market.

digitimes.com · Jul 3

Nvidia reportedly expands financing push with revenue-sharing model for AI cloud providers

Nvidia is expanding its financing efforts with a revenue-sharing model for AI cloud providers, offering financial guarantees in exchange for a share of their future cloud revenue. This initiative aims to support emerging GPU cloud providers and deepen Nvidia's role in the AI infrastructure market. The move is significant as it allows Nvidia to increase its presence in the growing AI market while providing financial support to emerging cloud providers. The revenue-sharing model is designed to help these providers build out their infrastructure. Nvidia's efforts are focused on the AI infrastructure market, which is rapidly expanding.

💡 Nvidia's revenue-sharing model creates a new path for emerging cloud providers to access funding and accelerate their growth. By taking a share of revenue, Nvidia aligns its interests with those of its partners, incentivizing mutual success.