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Nothing Raises $200M Series C to Power the Next Phase of Consumer AI

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Nothing Phone (3) aesthetic shot

Today, we’re announcing new funding––USD $200M in our Series C round at a USD $1.3B valuation. This milestone marks the start of our next phase: From being the only independent smartphone company to emerge in the last decade, towards building an AI-native platform in which hardware and software converge into a single intelligent system.

a portrait of Carl Pei, CEO and Co-founder of Nothing
Carl Pei, CEO and Co-founder of Nothing

Building the foundations for the future
When we started Nothing, we had a thesis that if we could build a smartphone business at scale and own the last-mile distribution point in consumer tech, we would be well-positioned for the next technology shift. Although we didn’t know what that would look like at the time, the opportunity is now crystal clear.

From the start, we knew that the foundation had to be an end-to-end value chain
capable of delivering products at speed, scale, and quality. As we’ve seen from many others that have tried, building a hardware company is hard. There are many potential failure points and almost no room for error. For us, it required assembling a team that balanced a pragmatic approach of rapidly launching products, with an innovative mindset to deliver experiences that our community would immediately love.

Today, the foundations are firmly in place. From award-winning design, to our global manufacturing and supply chain network built for quality and cost. In four years, we have shipped millions of devices, began 2025 crossing $1B+ in total sales, while growing 150% in 2024.

Building this infrastructure has been the hardest and most valuable thing we’ve done so far. With the support of our community, we’re fortunate to have made it here. Today, we’re in a position that will be very hard to copy: The ability to launch any consumer hardware product from start to finish within months, go-to-market operations that can ship and service worldwide, a global user community that co-creates with us, all without the innovator’s dilemma or bureaucratic constraints that the incumbents face. On to chapter 2.

Operating systems, evolved
In the last 18 years, the smartphone became ubiquitous. It is the primary personal computing tool to manage the countless tasks of daily life. Beyond its distribution scale, what makes the smartphone the most powerful consumer device in the market is its unmatched access to contextual information and user knowledge. For this reason, I believe the smartphone will remain one of the most important devices in the AI era.

On the other hand, while AI has made revolutionary progress in the last three years, the smartphone experience has barely evolved. Most of the innovation has been underwhelming, limited to incremental improvements in photo editing, translations, and assistant features that barely work.

For AI to reach its full potential, consumer hardware must reinvent itself alongside it. This is the opportunity we see for Nothing. We see a future where operating systems are significantly different from the ones today. Each system will know its user deeply, and be hyper-personalised to each individual. Interfaces will adapt to our context and needs. Suggestions will surface naturally, and once we confirm an intent, agents will execute on our behalf. The system will handle the non-essential for us, allowing us to focus on what truly matters, which will be different for every person. Unlike today’s one-size-fits-all solution, a billion different operating systems will be rendered for a billion different people.

Over time, this OS will be transversal across all form factors: We’re starting with smartphones, audio products and smart watches, devices that people already use every day. In the future, our OS will carry into smart glasses, humanoid robots, EVs, and whatever comes next.

Why we are uniquely-positioned to create this future: Owning the last-mile distribution point with all its contextual and user knowledge is essential to developing an OS that will help people in their daily lives. An AI OS that doesn’t know its user and isn’t ever-present can’t deliver a hyper-personalised experience. This is the next chapter for Nothing, integrating an AI experience into our hardware devices to reinvent how technology amplifies us.

The next billion unit scale product
In the near-term, we believe that the smartphone will remain the only device shipping at billion-unit scale each year. But soon, we’ll all be carrying an additional device that will be just as important. In the coming years, we’ll learn that the more context we can feed our AI, the more useful it becomes. The smartphone, while powerful, can’t always be there for us. Sometimes it’s in our pocket, or we might be on the move with our hands full.

A new class of AI-native devices will emerge. Products that are available to the user at the moment of need, paired with intelligence that turns understanding into action. This is a very exciting time, imagining devices that capture context across modalities and generate interfaces on demand, shaped by what the user is trying to accomplish.

We have been hard at work imagining what this future could look like, and can’t wait to launch some of our first AI-native devices next year.

Our Series C capital raise
This funding round allows us to execute on this vision by accelerating our innovation roadmap and further scaling our distribution. Our round was led by Tiger Global, with significant support from existing shareholders GV, Highland Europe, EQT, Latitude, I2BF, and Tapestry, alongside new strategic backing from Nikhil Kamath and Qualcomm Ventures.

Alongside this Series C, we’re also preparing to launch our next Community round giving our supporters another opportunity to become part of Nothing’s journey. More details will be shared soon.

As we continue our journey, we do so with huge gratitude to our community, our team, and our partners. This next chapter is only possible because of you.

Carl, CEO and Co-founder of Nothing

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Global Tech Leaders Unite to Propel Emerging Future-Critical Sectors at GITEX GLOBAL 2025

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GITEX Global

With capabilities of AI advancing every year, its potential to address challenges once thought unsolvable is rapidly expanding, from the possibility of curing genetic diseases to transforming urban mobility or enabling green data centres. With the global AI market set to reach $4.8 trillion by 2033 (UNCTAD), the race to deploy AI for critical sectors has never been more urgent. Against this backdrop, GITEX GLOBAL 2025 convenes as the world’s largest tech and AI event, with this year’s edition highlighting significant developments in biotech, physical AI, quantum computing, semiconductors, and data centres.

From 13-17 October at Dubai World Trade Centre, the show unites over 6,800 tech enterprises and 2,000 startups, with participation from 180 countries, bringing together the companies leading the world’s most ambitious AI infrastructure expansion. Global tech enterprises including Alibaba Cloud, AMD, AWS, Dell, e&, G42, Google, HPE, Huawei, IBM, Microsoft, Oracle, Salesforce, Siemens, and Snowflake anchor the showcase, with new incoming innovations from Cerebras, Datadog, Mitsubishi, Qualcomm, Rital, ServiceNow, Tata Electronics, Telecom Italia, and Tenstorrent.

Running in parallel is GITEX’s startup showcase, Expand North Star, from 12-15 October at Dubai Harbour, hosted by the Dubai Chamber of Digital Economy. Celebrating its 10th edition, the show connects 2,000 of the world’s most promising startups, with the highest percentage of growth & late-stage startups anywhere, with over 1,200 investors managing US$1.1 trillion assets. 

Trixie LohMirmand, EVP of DWTC, the organiser of GITEX globally, shared, “Future-critical sectors including data centres, biotech, quantum, and robotics are where AI ingenuity is converging with humanity’s most pressing challenges. GITEX GLOBAL 2025 gives new impetus to these transformative technologies, while continuing to being the harbinger of innovation-led progress across industries and global economies.”

Record Participation from Fast-Emerging Tech Economies – Brazil, Serbia, Chile

The show marks a record year for international participation, with Brazil joining as Country Partner with its largest-ever tech delegation, alongside the Serbian Chamber of Commerce and Industry and Tech Destination Pakistan as key partners. New pavilions debut from Canada, Chile, Ecuador, Spain, and Türkiye, in addition to expanded representation from Europe, Central Asia, LATAM, Africa, and the Levant.

Tatiana Riera, COO, ApexBrasil, shared: “ApexBrasil is excited to be at GITEX GLOBAL and Expand North Star with over 50 incredible startups and innovation hubs. It’s a great opportunity to show how Brazil is driving innovation and creating tech solutions for global challenges.”

Marko Čadež, President, Serbian Chamber of Commerce and Industry, added: “In the age of ubiquitous AI solutions, Serbian startups at this year’s edition demonstrate practical examples of AI applications across diverse fields: from well-being and energy to sentiment diagnostics on social media, showcasing the full depth and breadth of Serbian tech.”

Super Data Centres – The AI Factories of the Future

With global data centre investments set to exceed $500 billion in 2025 (BofA Research), GITEX GLOBAL welcomes one of the biggest global investors in this sector, O’Leary Ventures, building the world’s largest AI data centre industrial park in Canada. Paul Palandjian, CEO & Co-General Partner, O’Leary Ventures, commented: “The UAE has become the crossroads and a world leader in the development of technology and AI. No other place has the leadership vision, resources and commitment to attract a world-class cohort across every industry.” 

Adding a regional perspective, Hassan Alnaqbi, CEO of Khazna, MENA’s largest hyperscale data centre provider and a G42 company, leads the discussions on whether infrastructure, energy and policy can scale fast enough to keep pace with giga AI factories.

GITEX Digi Health & Biotech – The Next Frontiers of Medicine

Breakthroughs in gene editing, mRNA vaccines and AI-led drug discoveries are driving biotech spending towards $1.7 trillion in 2025 – setting the backdrop for the fastest AI deployment in this sector. At GITEX GLOBAL, Trevor Martin, CEO of Mammoth Biosciences, presents how CRISPR, their Nobel winning gene-editing technology, is using AI to potentially cure genetic diseases.
Matt Angle, CEO of Paradromics, the company behind the world’s first successful computer-brain implant, dives into decoding thought with AI and neurotech. Adding to this momentum, South Korean startup HurayPositive unveils AI-powered SaaS to deliver precision medicine for one million patients with chronic conditions.

Physical AI in Motion

At GITEX GLOBAL, Tensor unveils the world’s first personal robocar – globally applauded as “agentic AI on wheels”. Whilst K2 introduces new humanoids and a concept vehicle designed to extend robotics into industrial environments. With the robotics AI market projected to quadruple to $94 billion by 2031, these innovations illustrate how Physical AI is becoming an essential pillar of industry productivity and business edge.

GITEX Quantum Expo (GQX) – Advancing Quantum Readiness 

On the show floor, IBM unveils Quantum System Two, a major step towards large-scale fault-tolerant systems capable of solving computing scale challenges. Shukri Eid, VP and General Manager of IBM Gulf, Levant, and Pakistan, shared “GITEX GLOBAL is a global stage, but more importantly, it is a platform for action. It brings together the ecosystems that matter: policymakers, business leaders, and innovators driving AI forward.

Prof. Mark Thompson, Co-Founder of PsiQuantum, a $6 billion unicorn, outlines the path towards quantum sovereignty. Among the headline exhibitors is also IONQ, the world’s first public pure-play quantum computing company trading at the New York Stock Exchange.

Ai Semicon – The Chips Behind Sovereign AI

Global leader in high-performance processors, AMD presents its Instinct™ GPUs and EPYC™ CPUs, built to handle the most demanding AI workloads and energy-efficient data centre deployments. Jim Keller, CEO of Tenstorrent, the $2.6bn AI chipmaker on the Forbes AI50 List, expands on this theme with his talk on “Taking Control of Your Sovereign AI Future,” as semiconductors become a geopolitical lever.

Startups, Scaleups & Unicorns Lead in AI Supercomputing

Expand North Star features more than 40 unicorns this year, reinforcing the UAE’s position as a hub for global scale-ups. Among them, Cerebras presents the world’s largest AI supercomputer (built in partnership with G42), Fluidstack unveils the world’s first 1GW decarbonised AI supercomputer, and Xpanceo introduces five prototypes of AI-powered smart contact lenses -advancing AR, healthcare, and consumer hardware simultaneously.

For more information, visit: www.gitex.com.

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Bulwark & E-7 Cyber To Boost Cybersecurity In Middle East

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E-7-Cyber-and-Bulwark-Partnership

E-7 Cyber, a UK-based headquartered cybersecurity innovator, has announced a strategic partnership with Bulwark Distribution FZCO, one of the Middle East’s leading value-added distributors for IT and cybersecurity solutions. This collaboration represents a major step toward delivering next-generation security platforms to enterprises, government agencies, and organizations across the region.

The company’s flagship offerings include:

  • Blindspot: A next-generation data privacy solution designed to prevent insider-driven data leaks.
  • Vigilance: Advanced monitoring of critical data, enforcing identity-based digital footprints, and delivering comprehensive compliance tracking.
  • Regulatory Security Platforms: Streamlined solutions to ensure adherence to global and regional data protection regulations.

With these solutions, E-7 Cyber enables organizations to strengthen data protection, maintain regulatory compliance, and safeguard intellectual property in an increasingly complex digital landscape.

Strategic Partnership Pillars

The alliance is anchored on three strategic pillars:

  1. Market Expansion – Leveraging Bulwark’s strong channel network to expand the reach of E-7 Cyber’s enterprise-ready platforms across the MENA region.
  2. Cybersecurity Readiness – Addressing the surge in threats and compliance requirements driven by rapid digital transformation in the Middle East by offering advanced insider-threat prevention and regulatory security solutions.
  3. Digital Resilience – Delivering scalable, cost-effective platforms that help organizations defend against emerging risks while ensuring business continuity and compliance.

During the partnership, Heena Sharma, Chief Operations & Growth Officer of E-7 Cyber, quoted, “We are excited to partner with Bulwark, a trusted name in cybersecurity distribution. With this collaboration, we can scale our reach, bring our innovative data protection platforms to a wider audience, and help businesses in the Middle East strengthen compliance and insider-threat prevention.”

“We’re excited to partner with e-7 Cyber,” said Jose Menacherry, Managing Director at Bulwark Distribution FZCO. “This collaboration allows us to strengthen our security portfolio and better serve our customers’ needs for faster, more accurate threat protection including digital watermarking and protection.”

Strengthening Cybersecurity Across The MENA

The partnership focuses on making insider-threat prevention, data compliance, and access control technologies more accessible to enterprises and government agencies. As the GCC and wider Middle East undergo rapid digital transformation, businesses face increasing risks of insider leaks, identity theft, and complex regulations. This alliance addresses those challenges with enterprise-grade, compliance-driven solutions tailored to regional needs.

Value To Customers, Partners & Industry

Customers will gain access to advanced tools that enhance data protection, reduce risks, and simplify regulatory adherence. Channel partners benefit from an expanded portfolio of innovative solutions to meet rising demand. At the industry level, the collaboration strengthens the regional cybersecurity ecosystem by helping organizations combat insider threats, ensure compliance, and achieve secure growth.

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Unlock Business Value with GenAI Through a Data Semantic Approach

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By Robert Thanaraj, Sr Director Analyst at Gartner

Semantic representations of information are crucial for the functionality of large language models (LLMs), which is fuelling a heightened focus on semantics within data and analytics (D&A) and AI. 

Data silos become entrenched and limit an organization’s capacity to draw insights from its data. Without understanding the relationships within data, the individual pieces of information become less useful.

Semantic approaches facilitate a shared understanding of business terms and their interrelationships, which is vital for providing the necessary context for generative AI (GenAI). In a Gartner survey on the evolution of data management, 44% of the respondents from AI-ready organizations reported that semantic alignment is a key factor in assessing the AI readiness of their data.

D&A leaders can enhance and expand their semantic understanding by leveraging emerging technologies such as knowledge graphs and augmented data catalogs, thereby unlocking greater value from their information resources.

What is Data Semantics?

Data semantics refers to the meaning and interpretation of data within a business-specific context, as opposed to focusing on the physical representation of data through a data dictionary or a business glossary. It involves understanding what a data element represents, how it should be used, and its relationships with other data elements. Without this understanding, data is of limited use for AI use cases.

Semantic modeling is a practice of connecting technical metadata with business metadata.

A business glossary serves as the foundation for all things “semantic,” documenting the meanings of business-related terms. When the semantics and rules of a business glossary are well-understood, it leads to better data quality, easier integration and greater usefulness, supporting interactions with LLMs. The glossary also supports business goals like reducing costs and managing risks by making definitions clear, consistent and easy to trace back to their sources.

Top Recommendations for D&A leaders

  • -Upskill your data engineers with semantic modeling techniques such as the use of knowledge graphs in building business ontologies.
  • -Introduce DataOps practices to “deliver value from data” more easily, quickly and broadly. Take a people-, product- and governance-centric approach.
  • -Invest in converged data management platforms. Establish a platform engineering team that produces platform services for platform tenants.

Key Benefits of Data Semantics

Leveraging and governing semantics effectively enables:

  • Improved Data Understanding: Both people and applications gain a unified view of data and its structure. For example, if several medical e-commerce sites use consistent relationships between terms, applications can extract and aggregate information across these sites to support user queries or serve as input for other applications.
  • Knowledge Reuse: Relationships uncovered by one group can be reused or built upon by others for new use cases, allowing previously identified connections to be embedded in future work.
  • Enhanced Accuracy with LLMs:  Incorporating knowledge graphs into the training and inference processes of LLMs serves as a factual base (i.e., data and metadata source) for mitigating errors and hallucinations.
  • Enhanced Interoperability and Innovation: By adopting semantic modeling, organizations open themselves to a wider range of use cases and enable more effective data interchange.

Link Data from Different Sources to Derive Data Relationships

Semantic reconciliation plays a crucial role in effectively linking data from different sources. It is also essential for inferring relationships between disparate datasets. Without a clear understanding of the relationships, correlations and distinctions among the meanings of data from different modalities such as text, videos, images and structured data, organizations cannot fully realize the potential of their data assets.

Modern semantic tools use algorithms to find connections in data. These tools recommend the best ways to clean, organize and analyze information. They also track where data comes from and how it is used for better governance.

With augmented data discovery, algorithms automatically detect correlations, segments, clusters, outliers and relationships, presenting the most statistically significant and relevant results. By using these semantic approaches, organizations can connect information from different sources, uncover relationships and gain valuable insights that drive better decisions.

In business ecosystems, the degree of openness is driven by members’ strategies, common goals and shared interests. For example, governments, nongovernmental organizations, charities and community groups can collaborate on health or public policy issues, or in open-source developer communities. This creates an opportunity for exploiting the knowledge of data and the meaning of data in terms of what can be applied to several digital business moments.

Lastly Think Data Semantics Before Introducing Large Language Models

Organizations are spearheading transformative initiatives to implement large language models in order to transform their operations. However, data and analytics leaders often rush to integrate LLM capabilities without first ensuring these tools are aligned with real business outcomes. To maximize value, it’s essential to connect LLMs with robust semantic frameworks.

Knowledge graphs are a powerful foundation for leveraging LLMs in business contexts. These machine-readable data structures capture semantic knowledge about both physical and digital entities. These worlds include entities and their relationships, which adhere to a network of nodes and links forming the graph data model.

LLMs can streamline the creation of ontologies, which define categories and relationships within data. By using “few-shot” learning prompts—providing just a handful of examples—users can guide LLMs to generate base ontologies in open formats that suit their needs. These initial frameworks can then be refined for greater detail as required.

Additionally, LLMs support ontology mapping by helping users align entities and relationships across different datasets or systems. With targeted prompts and sample mappings, organizations can extract relevant connections from their data and improve accuracy through iterative refinement.

By adopting large language models alongside semantic representations like knowledge graphs and ontologies, organizations position themselves for faster deployment of advanced analytics solutions that deliver meaningful business value.

Check out our previous post NMK Interactive 2025 Sets New Middle East AV Benchmark

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