Executive Summary
• Anysphere weighs $30B valuation as Cursor hits $500M ARR: Sources say Anysphere is considering investment offers at a ~$30B valuation, with Cursor generating $500M ARR as of June, reportedly third-highest among AI apps. Highlights rapid enterprise adoption of AI coding tools and a potential step-change in sector valuations.
• US approves Nvidia chip exports to UAE in bilateral AI deal — Bloomberg: Eases a key export bottleneck and accelerates AI infrastructure buildout in the Gulf. Signals policy flexibility in US chip controls and sets the stage for a May 2025 bilateral AI pact with major implications for Nvidia’s growth and regional AI capacity.
• The Ethereum Foundation announces the 'Privacy cluster', a team of 47 blockchain industry experts developing protocol-level privacy features for the network: Addresses an emerging trend in AI and blockchain integration, crucial for future developments.
• TSMC Q3 revenue jumps 30% to $32.5B on AI demand: TSMC reported Q3 revenue of ~$32.5B, up 30% YoY and above estimates, driven by AI chip demand; Taipei-listed shares are up 34% YTD. Confirms sustained AI infrastructure tailwinds for the semiconductor supply chain.
• TSMC posts forecast-beating Q3 revenue surge on AI boom - Reuters: A 30%+ YoY revenue jump underscores structural AI demand for advanced nodes. TSMC is the linchpin of AI compute supply; this print validates continued capex cycles and tight leading-edge capacity.
• US approves several billion in Nvidia chip exports to UAE: BIS approved several billion dollars’ worth of Nvidia chip exports to the UAE, an early step in a planned May 2025 bilateral AI deal. Opens a significant Gulf market for Nvidia while diversifying demand amid tighter China restrictions.
• Sources: Microsoft is planning a major healthcare push for Copilot in partnership with Harvard Medical School, as it seeks to reduce its dependence on OpenAI (Sebastian Herrera/Wall Street Journal): A strategic verticalization of Copilot into regulated healthcare with top-tier partners, while hedging model dependency. This could unlock high-value clinical and admin use cases and reshape Microsoft’s AI stack control.
• Qualtrics to buy Press Ganey Forsta for $6.75B: Qualtrics plans a $6.75B acquisition of Press Ganey Forsta, expanding into healthcare outcomes and analytics. Adds substantial patient-experience data assets and cross-sell opportunities across Qualtrics’ enterprise base.
• n8n raises $180M at $2.5B valuation for AI automation: Berlin-based n8n secured $180M led by Accel at a $2.5B valuation to scale AI agents that automate repetitive tasks. Signals strong investor appetite for agentic automation platforms competing with Zapier/UiPath.
• Razorpay, NPCI, and OpenAI Launch Agentic Payments to Bring AI-Driven Commerce to India: Signifies collaborative efforts in integrating AI into commerce, impacting the financial landscape.
• OpenAI expands ChatGPT Go to 16 countries across Asia: OpenAI rolled out budget-friendly ChatGPT Go to 16 Asian markets, broadening reach to SMBs and consumers. Geographic expansion can lift paid user conversion and stabilize recurring revenue outside mature regions.
• Convergence: Human + AI for the Next Era of Finance - Boston Consulting Group: Explores the future relationship between AI and finance, relevant for industry leaders.
• Hyped AI business automation startup n8n raises $180M, valuing it at $2.5BN: Highlights the growing investment in AI automation, showcasing business trends and ROI potential.
• Perplexity moves 1T parameters between GPUs in 1.3 seconds: Perplexity demonstrated a trillion-parameter transfer across GPUs in 1.3s, showcasing high-throughput distributed training/inference. Points to efficiency gains that can cut training time and costs for large models.
• IBM expands agentic AI and infrastructure automation to bridge software, cloud and mainframe systems: Bridging mainframe to cloud with agentic AI targets the heart of enterprise IT. If successful, it accelerates modernization without rip-and-replace, unlocking ROI in complex, regulated environments.
• Samsung’s 7M-parameter Tiny Recursion Model outperforms o3-mini, Gemini: A 7M-parameter TRM beat much larger models like o3-mini and Gemini 2.5 Pro on ARC-AGI tasks. Suggests cost-effective, energy-efficient specialized models could challenge the scaling-is-everything narrative.
• Cloudera’s AI-in-a-Box gives enterprises a new way to build private AI: Packaged, private AI for data-resident industries addresses sovereignty and compliance barriers. A pragmatic path to productionizing AI behind the firewall for banks, healthcare, and government.
• Relace raises $23M to build infrastructure for AI coding agents: Relace secured $23M to develop infrastructure for AI coding agents. Funding supports core platform build-out in a fast-emerging developer agent ecosystem targeting software productivity gains.
• EU AI Act for Product Teams: Week-1 Guardrail Kit: Addresses regulatory impacts on AI adoption, crucial for businesses navigating compliance.
• ClickHouse extends Series C round to fuel real-time analytics and AI growth: Real-time analytics is the backbone of AI apps. Fresh capital to scale a high-performance OLAP database strengthens the data layer needed for low-latency AI products and observability.
• AnyTeam raises $10M from 40+ backers for AI sales: AnyTeam closed a $10M round backed by 40+ investors to scale AI sales automation. Validates growing demand for agentic tools that cut acquisition costs and accelerate revenue operations.
• How Visa wove AI into every facet of the company by approaching it as both a science and an art - Fortune: A blueprint from a global payments leader on scaling AI across fraud, personalization, and ops. Offers executives a concrete operating model for AI governance, culture, and measurable ROI.
• India's AI Boom Could Crash Without This One Crucial Change: Discusses potential risks in the AI landscape, relevant for stakeholders in the industry.
• AlgoX2 raises $3.5M to modernize data streaming infrastructure: AlgoX2 raised $3.5M to update data streaming for real-time AI workloads. Investment targets lower-latency pipelines essential for production-grade inference and analytics.
• During a Mumbai trade visit, UK PM Keir Starmer hailed India's digital ID program, Aadhaar, as a 'massive success' as the UK plans to introduce digital ID cards: Highlights successful government initiatives that impact social infrastructure and technology.
• Atlassian gives Rovo AI a major upgrade and developers new tools: Embedding AI into collaboration and dev workflows can compress cycle times and reduce context-switching. Atlassian’s platform reach makes this upgrade consequential for knowledge work productivity.
• Jentic first Irish startup joining AWS GenAI Accelerator cohort: Jentic became the first Irish company admitted to AWS’s GenAI accelerator. Access to AWS credits, tooling, and mentorship can speed productization and help expand Ireland’s AI startup footprint.
• A look at China's AI toy boom, which builds on decades of consumer electronics designed for children, as AI toy companies expand into the US and other markets (Caiwei Chen/MIT Technology Review): Shows how AI is entering early childhood products at scale, raising questions on safety, privacy, and educational value while signaling a new consumer category expanding globally.
• AWS selects three Indian startups for GenAI Accelerator program: AWS picked three Indian startups for its GenAI accelerator, providing resources and go-to-market support. Strengthens the region’s AI talent pipeline and accelerates commercialization of local AI solutions.
• ‘I’m a composer. Am I staring extinction in the face?’: classical music and AI: Captures the cultural and labor tensions in creative industries as generative AI challenges authorship, compensation, and the future of specialized artistic work.
• Anthropic pop-up draws 5,000 visitors, 10M impressions for Claude: Anthropic’s weeklong NYC pop-up attracted 5,000+ participants and 10M+ social impressions. Demonstrates strong consumer interest and brand lift that can translate to user growth for Claude.
• Paytm launches AI Soundbox for merchants in 11 languages: Paytm introduced an AI-powered Soundbox supporting 11 Indian languages, improving payment confirmations for merchants. Enhances usability and retention in India’s competitive merchant services market.
• Preliminary Report on Dangers of AI Chatbots - Psychiatric Times: Clinician-focused analysis of psychological risks from chatbots highlights safety gaps and informs product design, disclosure, and mental health policy.
• A121 Labs unveils Jamba Reasoning 3B model to cut costs: A121 Labs introduced Jamba Reasoning 3B, a compact model emphasizing reasoning with 3B parameters. Aims to deliver strong performance at lower compute/memory cost.
• HR vendor profile - a finger in Plum's view on the impact of AI: Delivers insights on AI's disruptive effects on HR practices, relevant for workforce management.
• Gnani.ai debuts AI avatars for HumanOS in Indic languages: Gnani.ai launched realistic AI avatars for HumanOS tailored to Indic languages. Targets localized customer support and onboarding, expanding addressable markets in multilingual regions.
• The ML Algorithm Selector: When to Use Which Machine Learning Algorithm: Educational content that appeals to a wide audience interested in practical AI applications.
• iFixit teardown shows $800 Meta Ray-Ban’s geometric waveguide system: A teardown of the $800 Meta Ray-Ban Display reveals a mirror-based geometric waveguide, differentiating its AR optics. Points to slimmer, more consumer-friendly AR devices that could pair with AI assistants.
• Google’s Gemini 2.5 Computer Use navigates web like humans: Google introduced a Gemini 2.5 mode capable of multi-step web navigation and actions. Advances practical agentic automation for tasks like RPA, support workflows, and enterprise process execution.
• Tresses of presidents, jewelry made from the locks of the dead find new homes as hair museum closes: A quirky story that showcases unusual applications of AI in cultural contexts.
Featured Stories
5 things Nvidia's Jensen Huang said about the state of the AI race with China - CNBC
In a recent CNBC article, Nvidia's CEO Jensen Huang addressed the ongoing AI race between the United States and China, highlighting key developments and challenges. This discourse is pivotal as it underscores the strategic importance of AI in global technological dominance and economic prosperity. The remarks come at a time when geopolitical tensions are influencing technological collaborations and supply chains, making AI a critical area of focus for both nations. Huang's insights shed light on the competitive dynamics at play and the potential for collaboration or conflict in advancing AI capabilities.
From a business perspective, Huang's comments underscore the critical role of Nvidia as a leader in AI hardware and software solutions. Nvidia's GPUs are at the heart of AI development, and the company's strategic positioning affects a wide array of industries, from autonomous vehicles to healthcare. The ongoing race with China could influence Nvidia's market strategies, partnerships, and investments in R&D. The potential for export restrictions or regulatory hurdles could also impact Nvidia's global operations and revenue streams. Companies reliant on Nvidia's technology must stay vigilant to these shifts, as they could affect supply chains and innovation cycles.
Technically, Huang highlighted the importance of maintaining a competitive edge through continuous innovation. Nvidia's advancements in AI chips, such as the development of more efficient and powerful GPUs, are crucial to keeping pace with China's growing technological prowess. The company's focus on AI frameworks and software ecosystems also plays a significant role in maintaining its leadership position. These innovations not only drive performance improvements but also enable new applications and use cases in AI, further entrenching Nvidia's influence in the tech sector.
The competitive landscape is shaped by the strategic maneuvers of both the U.S. and China as they vie for AI supremacy. Huang's remarks suggest a complex interplay of competition and potential collaboration, as both nations recognize the transformative potential of AI. The race could lead to accelerated innovation but also heighten tensions, impacting global technology markets and alliances. For Nvidia and other tech companies, navigating this landscape will require astute geopolitical awareness and strategic agility. Looking ahead, the future of AI will likely be defined by how well companies and nations manage these competitive pressures while fostering innovation and ethical advancements in the technology.
Sources: Microsoft is planning a major healthcare push for Copilot in partnership with Harvard Medical School, as it seeks to reduce its dependence on OpenAI (Sebastian Herrera/Wall Street Journal)
In a significant strategic move, Microsoft is reportedly planning to expand its Copilot AI initiative into the healthcare sector through a collaboration with Harvard Medical School. This development is noteworthy as it signals Microsoft's intention to diversify its AI capabilities and reduce its reliance on OpenAI. By partnering with a prestigious institution like Harvard Medical School, Microsoft aims to leverage cutting-edge medical research and expertise to enhance Copilot's functionality in healthcare settings. This initiative could potentially transform how healthcare professionals interact with technology, aiding in diagnostics, patient management, and administrative tasks, ultimately improving patient outcomes and operational efficiency.
The business implications of this move are substantial. By venturing into healthcare, a sector with enormous potential for AI integration, Microsoft is positioning itself to capture a significant share of the growing healthcare technology market. This initiative could lead to new revenue streams and strengthen Microsoft's foothold in the healthcare industry, which is increasingly embracing digital transformation. Additionally, by reducing its dependence on OpenAI, Microsoft seeks to assert more control over its AI development and strategic direction, potentially leading to more tailored and proprietary solutions that can be integrated across its suite of products and services.
From a technical perspective, this partnership could lead to the development of AI tools that are specifically optimized for the healthcare environment. Innovations might include advanced natural language processing capabilities for interpreting medical literature, machine learning algorithms for predictive analytics in patient care, and sophisticated data integration techniques for managing electronic health records. These technical advancements could enhance the accuracy and reliability of AI-driven healthcare solutions, ensuring they meet the rigorous standards required in medical contexts.
The competitive landscape in AI and healthcare technology could be significantly altered by Microsoft's move. By collaborating with Harvard Medical School, Microsoft not only gains access to a wealth of medical knowledge and research but also positions itself against competitors like Google and Amazon, which have also been making inroads into healthcare. This partnership could lead to a competitive advantage by offering solutions that are deeply informed by academic and clinical insights. As Microsoft strengthens its AI capabilities and expands its influence in healthcare, other technology and healthcare companies may need to accelerate their innovation efforts or seek similar partnerships to maintain their competitive edge.
Looking ahead, the implications of this initiative could be far-reaching. If successful, Microsoft's healthcare push with Copilot could pave the way for more specialized AI applications across various sectors, setting a precedent for how technology companies collaborate with academic institutions. Moreover, as AI becomes more integrated into healthcare, ethical considerations such as data privacy, algorithmic bias, and the role of human oversight will become increasingly important. Microsoft's approach to these challenges could influence industry standards and regulatory frameworks, shaping the future of AI in healthcare and beyond.
Business Impact: From a technical perspective, this partnership could lead to the development of AI tools that are specifically optimized for the healthcare environment. Innovations might include advanced natural language processing capabilities for interpreting medical literature, machine learning algorithms for predictive analytics in patient care, and sophisticated data integration techniques for managing electronic health records. These technical advancements could enhance the accuracy and reliability of AI-driven healthcare solutions, ensuring they meet the rigorous standards required in medical contexts.
A look at ASML's planned 100-hectare expansion project in Eindhoven, set to create 20,000 jobs and that is focused on expanding production of its EUV machines (Bloomberg)
US approves Nvidia chip exports to UAE in bilateral AI deal — Bloomberg
TSMC posts forecast-beating Q3 revenue surge on AI boom - Reuters
Sources: US Commerce Department's BIS approves several billion dollars' worth of Nvidia chip exports to the UAE, an early step in a May 2025 bilateral AI deal (Mackenzie Hawkins/Bloomberg)
In a significant development, the U.S. Commerce Department's Bureau of Industry and Security (BIS) has approved several billion dollars' worth of Nvidia chip exports to the United Arab Emirates (UAE). This decision marks an early step in a broader bilateral AI deal anticipated to be finalized by May 2025. The export approval underscores the strategic importance of AI technologies and the semiconductor industry in international relations and economic partnerships. For the UAE, obtaining advanced Nvidia chips represents a crucial step in its ambition to become a leading hub for AI innovation in the Middle East. Simultaneously, this move reflects the U.S.'s strategic intent to strengthen ties with the UAE, potentially as a counterbalance to China's growing influence in AI and semiconductor technology.
From a business perspective, the approval of these exports could significantly impact Nvidia's market position and financial performance. As a leading designer of graphics processing units (GPUs) and AI chips, Nvidia stands to benefit from increased revenue and strengthened partnerships in the Middle East. This deal not only opens up a lucrative market for Nvidia but also sets a precedent for other U.S. tech companies looking to expand their footprint in the region. Moreover, the deal may influence global semiconductor supply chains, particularly as the U.S. seeks to bolster its technological alliances with key partners amid ongoing geopolitical tensions. This could potentially lead to increased investment and collaboration in the semiconductor sector between the U.S. and UAE, fostering innovation and technological advancements.
Technically, the chips being exported are likely to include Nvidia's latest advancements in AI processing capabilities, such as its powerful GPUs designed for deep learning and neural network applications. These chips are pivotal for developing AI infrastructures, enabling high-performance computing, and fostering advancements in machine learning, data analytics, and autonomous systems. The introduction of such cutting-edge technology into the UAE's AI ecosystem could accelerate the development of smart cities, enhance security and surveillance systems, and drive innovation in sectors like healthcare, finance, and transportation.
The competitive landscape of the global AI and semiconductor industries may experience a shift as a result of this deal. By securing access to Nvidia's advanced chips, the UAE could enhance its competitive position in the AI sector, potentially challenging other regional players seeking to lead in AI development. On a global scale, this move could prompt other nations to seek similar partnerships, escalating the race for technological supremacy. Future implications of this deal include the potential for increased U.S.-UAE collaboration in AI research and development, which could lead to joint ventures, technology transfers, and the establishment of AI research centers. As AI continues to transform industries worldwide, partnerships like this one will be crucial in shaping the future of global technology and innovation.
Microsoft plans healthcare AI push in Copilot with Harvard deal: report
Hyped AI business automation startup n8n raises $180M, valuing it at $2.5BN
EU’s new AI strategies target industry adoption and research
The European Union has unveiled new strategies aimed at bolstering the adoption of artificial intelligence (AI) across industries while simultaneously enhancing research capabilities. This development is significant as it underscores the EU's commitment to positioning itself as a leader in the global AI landscape, a move motivated by both economic and strategic imperatives. By fostering an environment conducive to AI integration, the EU seeks to drive innovation, improve productivity, and maintain competitiveness in an increasingly digital world. This initiative is critical given the rapid advancements in AI technologies globally, particularly from the United States and China, which have dominated the AI sector in terms of investment and development.
From a business perspective, the EU's strategies are likely to stimulate a surge in AI-related investments across various sectors such as manufacturing, healthcare, and finance. By providing a framework that supports AI adoption, the EU is encouraging companies to integrate AI technologies into their operations, potentially leading to increased efficiency and cost savings. This could also lead to a proliferation of AI startups and an influx of talent into the region, further strengthening the EU's economic position. Moreover, the focus on research and development is expected to yield new AI innovations, providing European companies with a competitive edge in the global market.
On the technical front, the EU is emphasizing the importance of ethical AI and the development of frameworks that ensure AI systems are transparent, accountable, and aligned with European values. This focus on responsible AI development is crucial in addressing public concerns about privacy and the ethical use of AI. The strategies include initiatives to standardize AI technologies, which could facilitate interoperability and collaboration across borders. This standardization is essential for fostering innovation and ensuring that AI systems can be integrated seamlessly across different industries and applications.
The competitive landscape is poised to shift as the EU's strategies take effect. European companies may gain an advantage by operating within a region that prioritizes ethical AI and robust regulatory frameworks. This could attract global businesses seeking to align with these standards, potentially reshaping the global AI market dynamics. However, the EU will need to balance regulation with innovation to avoid stifling growth, a challenge that has been evident in other regulatory efforts.
Looking ahead, the EU's AI strategies could serve as a model for other regions seeking to harness AI's potential while addressing ethical and regulatory concerns. Successfully implementing these strategies could enhance the EU's influence in setting global AI standards and practices. However, the true test will be in execution and the EU's ability to foster collaboration among member states, academia, and industry stakeholders to drive meaningful progress in AI adoption and research.
Inside the rise of photonic computing powering next-gen AI workloads
The recent rise of photonic computing as a driving force behind next-generation AI workloads marks a significant technological milestone. Photonic computing leverages the properties of light for data processing, offering a paradigmatic shift from traditional electronic computing. This development is crucial as it addresses the escalating demand for higher computational power and efficiency required by complex AI models. The ability of photonic computing to process information at the speed of light, coupled with its potential for lower energy consumption, makes it a promising solution for overcoming the limitations of current electronic systems. This advancement matters because it could redefine the landscape of AI development, enabling more sophisticated and efficient machine learning models that could accelerate innovation across multiple sectors.
From a business perspective, the integration of photonic computing into AI workloads could lead to a significant competitive advantage for early adopters, particularly in industries reliant on high-speed data processing such as finance, healthcare, and autonomous technologies. Companies that invest in this technology may experience reduced operational costs due to its energy efficiency and enhanced capabilities in handling large-scale data analytics. This shift could disrupt existing market dynamics, prompting tech giants and startups alike to re-evaluate their R&D strategies and investment priorities. As the technology matures, it could catalyze new business models and revenue streams, particularly in cloud computing and AI-as-a-service offerings.
On the technical front, photonic computing introduces several innovations that distinguish it from traditional computing paradigms. By utilizing photonic integrated circuits (PICs), this technology can perform computations and data transfer with minimal latency and heat generation. Innovations such as silicon photonics and optical interconnects are at the forefront, enabling the development of compact and scalable photonic chips. These advancements not only enhance AI processing capabilities but also promote sustainability in computing by reducing the carbon footprint associated with data centers. However, the transition from electronic to photonic systems poses challenges in terms of manufacturing complexity and integration with existing digital infrastructure, necessitating further research and development.
The rise of photonic computing is poised to reshape the competitive landscape of technology industries. As more companies explore this frontier, we may see increased collaborations and partnerships between tech firms, academic institutions, and government bodies to accelerate research and commercialization. This could lead to a race for intellectual property rights and standard-setting, influencing market leaders and newcomers alike. Looking ahead, the future implications of photonic computing are profound. It has the potential to unlock unprecedented levels of computational power, facilitating breakthroughs in AI that could transform industries, enhance human-machine interactions, and drive global economic growth. As the technology evolves, stakeholders must navigate the challenges and opportunities it presents to harness its full potential effectively.
OpenAI expands its ~$5 ChatGPT Go plan to 16 new Asian countries, including Malaysia, Pakistan, the Philippines, and Vietnam, after launching it in August (Ivan Mehta/TechCrunch)
Gnani.ai Debuts Realistic AI Avatars in Indic Languages with HumanOS
Gnani.ai's introduction of realistic AI avatars in Indic languages, powered by their HumanOS platform, marks a significant milestone in the AI and language technology sectors. This development is noteworthy as it addresses the increasing demand for digital solutions that cater to the linguistic diversity of the Indian subcontinent. By enabling AI avatars to communicate in multiple Indic languages, Gnani.ai is not only enhancing user engagement but also fostering inclusivity in digital interactions. This advancement is critical as it aligns with the broader trend of localizing technology to meet the needs of diverse linguistic groups, which is especially pertinent in a country like India with its vast array of languages.
From a business perspective, Gnani.ai's innovation could open new revenue streams and expand their market reach. By offering AI solutions that are tailored to regional languages, they position themselves as key players in sectors such as e-commerce, customer service, and education, where personalized and accessible communication is crucial. This development could potentially disrupt the market by setting a new standard for AI-driven communication tools, prompting other companies to invest in similar technologies to remain competitive. Furthermore, it could attract partnerships with enterprises seeking to enhance their customer interactions in local languages, thereby increasing Gnani.ai's influence and market share.
Technically, the introduction of realistic AI avatars capable of conversing in Indic languages involves sophisticated natural language processing (NLP) algorithms and speech synthesis technologies. The HumanOS platform likely utilizes advanced machine learning models trained on extensive datasets of Indic languages to ensure accurate and natural-sounding speech. This innovation not only demonstrates Gnani.ai's technical prowess but also highlights the importance of developing AI systems that can handle the complexities of tonal and dialectical variations inherent in Indic languages. The ability to create realistic avatars that can seamlessly interact in multiple languages is a testament to the progress in AI-driven language processing and avatar realism.
In terms of the competitive landscape, Gnani.ai's initiative could spur increased competition among AI firms in India and beyond, as companies strive to enhance their language capabilities and avatar realism. This move might catalyze further advancements in AI language processing and avatar technology, pushing competitors to innovate and improve their offerings. As the demand for localized digital solutions grows, we can expect to see more players entering this space, potentially leading to strategic partnerships and collaborations to leverage complementary strengths and technologies. In the long run, Gnani.ai's breakthrough could set a precedent for the development of AI technologies that prioritize linguistic diversity and user-centric design, influencing future trends in the AI industry.
Tiny Model from Samsung AI Lab Beats Gemini 2.5 Pro, o3-mini on ARC-AGI
CoreWeave to Acquire Monolith, Expanding AI Cloud Platform into Industrial Innovation - Yahoo Finance
NetSuite expands SuiteCloud Platform with New AI Innovations
NetSuite's recent expansion of its SuiteCloud Platform with new AI innovations marks a significant development in the enterprise resource planning (ERP) landscape. This move underscores the increasing integration of artificial intelligence into business management software, aiming to enhance operational efficiency and decision-making processes. By incorporating AI capabilities, NetSuite seeks to provide its users with advanced data analytics, predictive insights, and automation features that can streamline workflows and reduce manual errors. This development is crucial as businesses across various sectors are continually seeking ways to leverage AI to stay competitive and agile in a rapidly evolving digital economy.
From a business perspective, the introduction of AI features into the SuiteCloud Platform could have wide-reaching implications for NetSuite's market positioning. By enhancing its product offerings with AI, NetSuite not only strengthens its value proposition but also potentially attracts a broader customer base looking for cutting-edge technological solutions. This could lead to increased market share and customer retention as businesses are drawn to platforms that promise improved efficiency and innovation. Furthermore, these AI enhancements could enable businesses to better harness their data, leading to more informed decision-making and potentially significant cost savings. This move could also pressure competitors to accelerate their AI integration efforts to maintain relevance.
Technically, the AI innovations in the SuiteCloud Platform likely involve advanced machine learning algorithms and natural language processing capabilities, which can offer predictive analytics and automated insights. These technologies enable the platform to process large volumes of data quickly and generate actionable insights, allowing businesses to anticipate market trends and consumer behavior more accurately. Additionally, automation features powered by AI can reduce the burden of routine tasks, freeing up human resources for more strategic activities. This technical advancement not only enhances the functionality of the SuiteCloud Platform but also sets a new standard for what businesses can expect from ERP systems.
In terms of the competitive landscape, this strategic enhancement by NetSuite could disrupt the ERP market by setting a precedent for AI integration. Competitors like SAP, Microsoft Dynamics, and Oracle may need to expedite their AI innovation strategies to keep pace with NetSuite's advancements. This could lead to a technological arms race within the ERP sector, with companies striving to outdo each other in terms of AI capabilities and offerings. As AI becomes more embedded in business platforms, the future implications could include a significant shift in how businesses operate, with AI-driven insights becoming central to strategic planning and execution. This shift could redefine competitive dynamics across industries, as businesses that effectively leverage AI could achieve superior performance and market leadership.
A121 Labs’ Jamba Reasoning 3B is a powerful tiny model that promises to transform AI economics
IBM expands agentic AI and infrastructure automation to bridge software, cloud and mainframe systems
PagerDuty debuts end-to-end AI agents to automate and accelerate incident management
Dell builds momentum behind AI factories for the data center era
In the article titled "Dell builds momentum behind AI factories for the data center era" from SiliconAngle AI, Dell Technologies is reported to be advancing its efforts in establishing AI factories, which are essentially data centers optimized for artificial intelligence workloads. This development is significant as it highlights Dell's strategic pivot towards embracing AI as a core component of its data center offerings. The move reflects the growing demand for AI-driven solutions and the need for infrastructure that can support the immense computational requirements of AI applications. This initiative is crucial as it positions Dell to cater to enterprises seeking to leverage AI for competitive advantages, thereby reinforcing its role as a key player in the digital transformation landscape.
From a business perspective, Dell's focus on AI factories could have substantial implications for the market. By providing infrastructure that can efficiently handle AI workloads, Dell is likely to attract a diverse clientele, including industries such as healthcare, finance, and manufacturing, which are increasingly adopting AI for various applications. This could lead to increased revenue streams and potentially elevate Dell's market share in the data center sector. Furthermore, by investing in AI-centric infrastructure, Dell is aligning itself with the broader industry trend towards AI and machine learning, ensuring its relevance in a rapidly evolving technological landscape. This strategic move could also pressure competitors to enhance their offerings, thereby driving innovation across the industry.
Technically, the AI factories being developed by Dell are expected to incorporate cutting-edge innovations in hardware and software designed to optimize AI processing. This includes leveraging advanced GPUs, specialized AI accelerators, and high-speed networking to handle the vast amounts of data processed by AI algorithms. Additionally, Dell's emphasis on scalable and flexible architectures will allow enterprises to tailor their AI infrastructure to specific needs, improving efficiency and performance. As AI workloads continue to grow in complexity and scale, the ability to provide robust, flexible, and high-performance data center solutions will be critical.
In terms of the competitive landscape, Dell's initiative could spur other major technology companies to accelerate their own AI infrastructure development efforts. Companies like IBM, HPE, and Cisco might respond by enhancing their data center solutions to maintain competitive parity. Moreover, cloud service providers such as AWS, Google Cloud, and Microsoft Azure, which already offer AI-optimized infrastructure, could face increased competition from Dell's on-premise solutions. This could lead to a competitive environment characterized by rapid innovation and potentially lower prices, benefiting end users.
Looking ahead, Dell's push into AI factories is likely to have long-term implications for the data center industry. As AI continues to permeate various sectors, the demand for specialized infrastructure will grow, and companies that can deliver efficient, scalable solutions will be well-positioned for success. Furthermore, Dell's efforts may catalyze a broader shift towards AI-optimized infrastructure, encouraging more enterprises to adopt AI technologies and integrate them into their operations. This could lead to increased productivity and innovation across industries, driving economic growth and transformation in the coming years.
UAE, Singapore lead AI adoption while U.S. lags despite dominance in innovation
AI And The End Of Progress? Why Innovation May Be More Fragile Than We Think - Forbes
The Forbes article titled "AI And The End Of Progress? Why Innovation May Be More Fragile Than We Think" explores the notion that the rapid advancements in artificial intelligence (AI), while groundbreaking, may be more vulnerable than they appear. The article posits that the current trajectory of AI development might encounter significant hurdles due to factors such as regulatory challenges, ethical concerns, and the limitations of existing technological infrastructure. This matters because AI is not only a driver of innovation across multiple industries but also a critical component of national economic strategies. The potential stagnation or slowing of AI advancement could have widespread implications for global competitiveness and economic growth.
From a business perspective, the fragility of AI innovation could lead to increased caution in investment and development strategies. Companies heavily relying on AI for competitive advantage may face uncertainty if progress stalls, potentially affecting everything from product development timelines to market positioning. This could also impact stock valuations and investor confidence, as firms may need to recalibrate their growth projections and strategic priorities. Moreover, industries such as healthcare, finance, and manufacturing, which are increasingly dependent on AI technologies, might experience slower efficiency gains and innovation cycles, affecting their bottom lines.
On the technical front, the article highlights concerns regarding the scalability and sustainability of current AI models. As AI systems become more complex, they require exponentially greater computational resources, which could lead to bottlenecks in both energy consumption and data processing capabilities. Innovations such as quantum computing and neuromorphic chips are still in nascent stages and may not be ready to address these challenges in the immediate future. The article suggests that without significant breakthroughs in these areas, the pace of AI innovation may decelerate, impacting the overall technological landscape.
In terms of the competitive landscape, the fragility of AI innovation could alter the dynamics between tech giants and smaller startups. Larger companies with substantial resources may consolidate their positions by acquiring key technologies or talent, potentially stifling competition and innovation from smaller players. This could lead to a more monopolistic market structure, reducing diversity in AI solutions and approaches. Additionally, geopolitical tensions could exacerbate these issues, as countries vie for AI supremacy, potentially leading to fragmented global AI ecosystems.
Looking ahead, the article suggests that stakeholders in the AI ecosystem need to adopt a more sustainable approach to innovation. This includes investing in foundational research, fostering open collaboration between academia and industry, and developing robust regulatory frameworks that balance innovation with ethical considerations. The future implications of AI's fragility underscore the importance of resilience and adaptability in technological advancement, ensuring that progress continues in a manner that is both inclusive and sustainable.
Cloudera’s AI-in-a-Box gives enterprises a new way to build private AI
'Buckle up': IMF and Bank of England join growing chorus warning of an AI bubble - CNBC
Relace wants to build the infrastructure foundation for AI coding agents after raising $23M in funding
Relace, a burgeoning company in the AI space, has recently secured $23 million in funding to develop a foundational infrastructure for AI coding agents. This development is significant as it indicates a growing interest and investment in automated coding solutions, which promise to transform software development processes by leveraging AI capabilities. The funding round highlights investor confidence in Relace's vision to streamline and enhance the coding landscape, potentially reducing the time and resources required for software development. This move is pivotal as it addresses a critical need for efficiency and scalability in software engineering, which is increasingly important in a digitally driven world.
From a business perspective, Relace's initiative could have a profound impact on the software development market. By providing a robust infrastructure for AI coding agents, the company positions itself as a key player in an emerging industry that seeks to automate repetitive coding tasks, thus freeing up human developers to focus on more complex and creative aspects of software creation. This could lead to increased productivity and innovation within tech companies, as well as cost reductions due to decreased reliance on human labor for routine coding tasks. Moreover, as organizations across various sectors continue to adopt AI solutions, Relace's infrastructure could become an integral part of the tech stack for businesses looking to stay competitive in an AI-driven market.
Technically, Relace's approach involves building a scalable and reliable infrastructure that supports the deployment and operation of AI coding agents. This includes developing sophisticated algorithms capable of understanding and generating code, as well as creating a seamless integration with existing development environments. The innovation lies in the ability to automate complex coding tasks while maintaining high standards of code quality and performance. By addressing challenges such as code context understanding and error handling, Relace aims to create AI agents that can work alongside human developers, augmenting their capabilities and enhancing overall productivity.
In terms of the competitive landscape, Relace's advancements could disrupt traditional software development paradigms and challenge existing players in the coding tools and platforms market. Companies that have traditionally relied on human developers may need to adapt quickly to incorporate AI-driven solutions or risk falling behind. Additionally, this development could spur further innovation and competition as other companies seek to develop their own AI coding solutions, leading to a dynamic and rapidly evolving market. The future implications of Relace's work are significant, as successful implementation of AI coding agents could redefine how software is developed, leading to a more efficient and innovative tech industry. As AI continues to evolve, the potential for these coding agents to tackle increasingly complex tasks will grow, further solidifying their role in the future of software development.
A survey of 1,000 ninth through 12th grade US students finds that nearly one in five say they or someone they know has had a romantic relationship with AI (Lee V. Gaines/NPR)
Other AI Interesting Developments of the Day
Business & Enterprise
• Convergence: Human + AI for the Next Era of Finance - Boston Consulting Group
• IBM expands agentic AI to bridge mainframes, cloud and software
• Microsoft plans Copilot healthcare push with Harvard Medical School
• Razorpay, NPCI, OpenAI launch agentic payments for India commerce
• Oracle NetSuite overhauls user experience, introduces AI-driven updates
• Paytm Launches AI-Powered Soundbox for Merchants in 11 Indian Languages
• Visa embeds AI across company, reshaping fraud and payments
• n8n raises $180M at $2.5B valuation to scale AI agents
• NetSuite expands SuiteCloud platform with new AI innovations
• Beyond the PoC: AI agents put enterprise automation to the test
• CoreWeave to acquire Monolith, expand AI cloud into industrial
• Zendesk launches AI automation features for contact centers
• Partners in cloud: Why co-innovation is critical to unlocking AI's potential
• Turning AI from theory to ROI: The rise of practical enterprise adoption models
• SoCal Edison, GreenShield deploy agentic AI to automate operations
• Hyped AI business automation startup n8n raises $180M, valuing it at $2.5BN
• Dataiku launches Agent Hub to control agentic AI automation
• Cloudera launches 'AI-in-a-Box' for private enterprise AI deployments
• AWS selects 3 Indian startups for GenAI accelerator programme
• Anthropic's AI safety tool Petri uses autonomous agents to study model behavior
• Nvidia unveils AI factory vision to power enterprise computing
• PagerDuty debuts end-to-end AI agents to automate incident management
• Ukrainian Takes Sumo By Storm After Fleeing War To Pursue Dreams
• TSMC Q3 sales seen to beat estimates on AI chip demand
• Paytm Launches AI-Powered Soundbox for Merchants in 11 Indian Languages
• EU unveils new AI strategies to boost industry adoption, research
• UAE, Singapore lead AI adoption; U.S. trails despite innovation
• AI sales automation startup AnyTeam gets $10M backing from 40+ investors
Human Interest & Social Impact
• Gnani.ai launches HumanOS avatars for 10+ Indic languages
• India's AI boom risks collapse without one crucial change
• EU unveils new AI strategies to boost industry adoption, research
• Aadhaar reaches 1.3B users; UK hails digital ID success
• Ethereum Foundation forms Privacy cluster with 47 experts
• Anthropic launches Petri safety tool using autonomous agents
• EU AI Act Week-1 guardrail kit released for product teams
• IBM expands agentic AI across 3 system domains: cloud, mainframe
• Plum advises HR: AI will reshape key hiring attributes
• Agentic AI enters classrooms, automating administrative tasks
• Six lawtech firms push legal sector into AI era
• LLMs Don’t Think. They Just Get Lucky.
• Classical composers warn AI threatens creative jobs, livelihoods
• Psychiatric Times issues 1st preliminary report on chatbot dangers
• Paytm Launches AI-Powered Soundbox for Merchants in 11 Indian Languages
Developer & Technical Tools
• Pulumi debuts first AI agents for cloud platform engineering
• Perplexity Transferred a Trillion Parameters Between GPUs in Just 1.3s
• PagerDuty debuts end-to-end AI agents to automate incidents
• Automation reaches the classroom: How agentic AI is redefining operational efficiency
• Google unveils Gemini 2.5 Computer Use model that navigates web
• IBM expands agentic AI and automation across cloud and mainframes
• Samsung AI Lab tiny model beats Gemini 2.5 Pro on ARC-AGI
• New reports add to concerns about potential AI bubble
• A121 Labs releases Jamba Reasoning 3B tiny model with reasoning
• Dataiku launches Agent Hub to manage agentic AI automation
• ClickHouse extends Series C to fuel real-time analytics and AI growth
• Anthropic launches Petri safety tool using autonomous agents to test models
• Hugging Face Transformers framework redefines modern AI development
• Everyone can go build: Retool adds latest chapter in movement to democratize software generation
• Atlassian upgrades Rovo AI adding new developer tools and APIs
• Relace wants to build the infrastructure foundation for AI coding agents after raising $23M
• Retool launches generative tools to democratize software generation
• FormAssembly launches AI assistant to streamline data collection workflows
• Michael Dell on the unstoppable rise of AI factories
• Spacelift enables instant 'codeless' infra provisioning for cloud workloads
• JumpCloud adds asset management solution to expand IT toolkit
Education & Compliance
• Six companies pushing the legal world into the AI era
• EU AI Act releases Week-1 Guardrail Kit for Product Teams
• Psychiatric Times issues preliminary report on AI chatbot safety risks
• BCG recommends human+AI convergence for next era of finance
• US approves Nvidia chip exports to UAE in AI deal
• UK plans digital ID cards after praising India's Aadhaar program
• Generative AI : A Beginners Viewpoint
• Ethereum Foundation launches Privacy cluster with 47 blockchain experts
• EU leverages regulation and industry strengths to shape AI future
• JumpCloud launches asset management solution to centralize IT inventory
• India warns: one crucial AI policy change needed to sustain boom
• Opkey expands Argano partnership to accelerate Oracle automation
• Neocloud strategies reshape the future of compute efficiency
• AI agents fail key enterprise PoC tests, raising governance alarm
• Plum warns AI will reshape hiring skills, urges retraining
• Hugging Face Transformers: The Framework Redefined Modern AI
• M&A enterprises get five AI deployment tips for governance
• Developer Experience article outlines 6 AI-induced challenges for teams
• Stop Scrolling — This Is the Only Small Language Model Article You’ll Ever Need
Research & Innovation
• Perplexity Transferred a Trillion Parameters Between GPUs in Just 1.3s
• A121 Labs launches Jamba Reasoning 3B tiny model
• Photonic computing enables next-gen AI workloads with optical accelerators
• Hugging Face Transformers framework redefined modern AI model development
• Multidimensional computing advances AI factory design beyond linear limits
• Neocloud strategies reshape compute efficiency for AI at scale
• Small language models guide outlines compact LLM tradeoffs and benchmarks
• Google's Gemini 2.5 Computer Use model can navigate the web like a human
• LLMs paper argues models 'get lucky' on reasoning, not thinking
• Scientists propose brain operates with 7 senses instead of five
• Cloudera's AI-in-a-Box gives enterprises a new way to build private AI
• n8n raises $180M at $2.5B valuation for AI agents
• Exclusive: FormAssembly launches AI assistant to streamline data collection
• OpenAI launches budget ChatGPT across 16 Asian countries
• Microsoft plans Copilot healthcare push via Harvard partnership
• PagerDuty debuts end-to-end AI agents to automate and accelerate incident management
• Italy adopts AI law with national algorithm guardrails
AWS Cloud & AI
• AWS launches Quick Suite replacing Q Business for enterprise AI
• AWS unveils agentic AI hub searchable across enterprise data
• AWS Quick Suite, Google Gemini Enterprise clash for full-stack AI
• Secure LangChain APIs with AWS SSO and Active Directory integration
• AWS launches Skills Profile on Skill Builder tracking skills across roles
• Jentic joins AWS Gen AI Accelerator as first Irish startup
• AWS introduces IAM access analysis and reports for governance
• Desplegando con AWS CDK + EC2 (Guía paso a paso para principiantes)
Azure Cloud & AI
• Azure launches NVIDIA GB300 NVL72 cluster for OpenAI
• Azure deploys NVIDIA GB300 NVL72 cluster for OpenAI
• Microsoft outage cripples Teams, Minecraft, Microsoft 365 services
• Azure outage blocks Microsoft 365, admin portals globally
• Azure retires AI Health Insights and associated models
• Microsoft Azure deploys first large-scale cluster of Nvidia GB300 for OpenAI workloads
• Azure Arc reaches GA for firmware analysis with automation
• Strengthening Cloud Security: Authenticating Terraform to Azure Using a Service Principal
• Google Cloud targets Microsoft, OpenAI in workplace AI market
• Microsoft engineer resigns over Azure cloud work with Israeli military
• Microsoft commits to expand cloud infrastructure capacity in Asia
• [Launched] Generally Available: Custom port support for Azure Database for MySQL – Flexible Server
GCP Cloud & AI
• Google Cloud launches Gemini Enterprise at $30/user/month for employees
• Google Cloud unveils Gemini Enterprise agentic platform for enterprises
• Google Cloud opens Gemini Enterprise partner ecosystem with integrations
• Google Cloud unveils Gemini Enterprise as Accenture deal accelerates adoption
• Figma partners with Google Cloud to expand AI-powered design tools
• Google Cloud CEO Kurian outlines Gemini Enterprise strategy, labor impacts
• Google Cloud Battles Microsoft, OpenAI for Workplace AI
• Google Cloud launches AI Arena Impact Challenge to spur enterprise AI
Security & Costs
• Researchers Woolley and Jackson warn AI election threats
• US approves Nvidia chip exports to UAE in bilateral AI deal — Bloomberg
• AI agents move beyond PoC, test enterprise automation ROI
• Taiwan Semiconductor Q3 sales seen to beat estimates on AI
• China honing abilities for a possible future attack, Taiwan defence report warns - Reuters
• Nvidia’s Jensen Huang outlines 5 AI race warnings with China
• Neocloud strategies reshape compute efficiency, cut multi-cloud costs
• Dataiku’s new Agent Hub gives businesses full control over agentic AI automation
• Spacelift launches instant codeless provisioning for cloud workloads
• Dell builds AI factories to cut data center TCO
• 'Sending You Love From Gaza': Palestinians Hail Ceasefire Deal
• Cloud partners push co-innovation to lower AI infrastructure costs
• Zendesk introduces new AI automation features for contact centers
• New reports warn of AI bubble risks hitting valuations, spending
• Italy adopts AI law tightening rules for high-risk systems
• Building future-fit organizations through an AI-first mindset
AI News in Brief
• OpenAI and Nvidia mega-deals fuel AI arms race, bubble fears: What specifically happened: reporting on large, multi‑billion dollar deals between OpenAI and Nvidia that concentrate GPU capacity and ecosystem incentives. Key facts: these mega-deals lock huge amounts of cutting‑edge compute and preferential access to training hardware. Concrete impact: centralizes infrastructure power, boosts incumbents’ advantage, escalates bidding for chips/cloud, and raises systemic risk of a compute‑driven valuation loop (potential circular bubble) affecting startups, cloud providers, and chip supply chains.
• Google ignores hidden Gemini AI exploit letting hackers control text: What specifically happened: reports claim Google ignored a discovered Gemini vulnerability that lets attackers manipulate model outputs via crafted inputs. Key facts: the exploit enables external actors to alter text generation behavior and potentially execute prompt‑injection style attacks. Concrete impact: raises immediate security concerns for enterprises deploying Gemini for search, assistants, or workflows, increases risk of data leakage and poisoned outputs, and pressures Google to patch or face enterprise trust/contract fallout.
• Cisco launches 8223 Routing System to link AI data centers: What specifically happened: Cisco announced the 8223 Routing System, a new networking product targeted at AI data center connectivity. Key facts: the 8223 is positioned as a high‑capacity router purpose‑built to handle AI traffic between clusters and cloud regions. Concrete impact: provides operators a scalable networking option for large inference/training workloads, accelerates deployment of AI data centers, and influences vendor choices for hyperscalers and enterprise AI infrastructure.
• Spellbook raises $50M at $350M valuation, ~4,000 customers: What specifically happened: Toronto‑based Spellbook raised $50M in a financing round led by Khosla Ventures at a $350M valuation and reported roughly 4,000 customers. Key facts: $50M raise, $350M valuation, ~4,000 customers. Concrete impact: validates strong demand for AI legal‑contract tools, provides capital for product expansion and scaling, and signals investor appetite for vertical generative AI SaaS with measurable customer traction.
• Ex-OpenAI researcher builds $1.5B hedge fund, huge influence: What specifically happened: a 23‑year‑old former OpenAI researcher leveraged a viral AI prediction to build a hedge fund reported at $1.5B in assets, gaining notable Silicon Valley and Washington influence. Key facts: $1.5B fund, founder’s OpenAI pedigree and public profile. Concrete impact: demonstrates how individual AI narratives can rapidly convert into large capital pools influencing policy, investment, and startup ecosystems, and concentrates influence between finance and AI research communities.
• Q3 venture funding jumps 38% as AI giants garner massive rounds: Crunchbase reporting shows Q3 venture funding rose 38%, driven by very large rounds directed at AI incumbents and platform bets; the concentration of capital into mega-rounds and exits is reshaping the startup landscape, making it harder for early-stage entrants to compete and amplifying valuation and liquidity distortions across the AI funding market.
• n8n raises $180M to expand amid OpenAI competition: What specifically happened: automation platform n8n completed a $180M funding round as it scales its automation and integration tooling in an era of fast‑evolving AI competitors. Key facts: $180M raise. Concrete impact: fuels product development and go‑to‑market expansion, helps n8n compete with larger vendors building AI‑powered automation, and highlights investor willingness to back orchestration layers that integrate generative AI with enterprise data.
• IMF and Bank of England warn of AI bubble risk: Both the IMF and the Bank of England publicly cautioned that rapid capital inflows and sky-high valuations tied to AI could constitute a bubble; these macro-level warnings elevate the likelihood of tighter policy scrutiny, investor re-rating risk for AI assets, and potential regulatory interventions that could slow funding and hiring in the sector.
• Disney opts out of OpenAI's Sora app, CAA warns artists: What specifically happened: sources report Disney declined to allow its IP into OpenAI’s Sora app and talent agency CAA warned that Sora exposes artists to 'significant risk.' Key facts: Disney opt‑out and CAA public objection. Concrete impact: underscores rising licensing and consent battles between content owners and generative AI platforms, may slow dataset access for models, and forces AI firms to negotiate stricter content deals or face legal/PR backlash.
• Oracle NetSuite launches AI-driven UX overhaul across ERP customers: What specifically happened: Oracle announced an AI‑driven user experience overhaul for its NetSuite ERP suite, embedding generative capabilities into workflows. Key facts: platform‑level AI UX changes across NetSuite customers (announcement). Concrete impact: accelerates AI adoption in back‑office functions, promises productivity gains for finance/operations teams, and intensifies competition in enterprise ERP by making AI features a product differentiator.
• 1Password unveils fix for AI agents leaking passwords, claims block: What specifically happened: 1Password announced a solution aimed at preventing AI agents from exfiltrating stored credentials. Key facts: product update targets AI agent password‑leak vectors. Concrete impact: addresses a critical security vector as enterprises adopt autonomous agents, reduces risk of credential leakage in AI‑driven workflows, and could become a required control for secure AI deployments.
• Coding Agent Teams emerge as next frontier in AI-assisted development: Industry coverage highlights the rise of coordinated 'coding agent teams'—multiple autonomous code-writing agents collaborating on software projects; this trend changes the software development lifecycle by automating multi-step engineering tasks, raising productivity but also creating new orchestration, testing, and security challenges that will drive tooling and platform innovation.
• Michael Dell warns of unstoppable rise of AI factories industry: What specifically happened: Michael Dell publicly framed a new wave of 'AI factories'—integrated, production‑scale AI stacks—as an unstoppable industry trend. Key facts: Dell’s industry perspective and vendor positioning toward factory‑like AI deployments. Concrete impact: signals strong server, storage, and services demand; guides enterprise IT strategy toward turnkey AI platforms; and pressures OEMs, cloud providers, and system integrators to deliver end‑to‑end AI solutions.