Meta is taking the next step in the AI ​​race by creating a lab dedicated to superintelligence. The goal? To surpass human capabilities and deliver "personal superintelligence for all." Creation of Meta Superintelligence Labs For several months, Meta has been nurturing ambitious ambitions in artificial intelligence. The company led by Mark Zuckerberg has just reached a new milestone by formalizing the creation of Meta Superintelligence Labs. This unique laboratory aims to develop "superintelligence"-level AI systems, surpassing human performance and capable of reasoning, learning, and adapting autonomously and multimodally. This initiative marks a strategic step in the rivalry between Meta, OpenAI, Google DeepMind, and Anthropic. It is part of Meta's desire to reposition its technology portfolio and become a key player in the field of advanced artificial intelligence. By bringing together its R&D teams from FAIR and its product divisions, Meta is completely restructuring its AI strategy to accelerate the development of Llama 4 and 5-type models, while designing cross-functional applications capable of simultaneously processing text, images, video, voice, and sensory data. An Unprecedented War for Talent To support this ambitious project, Meta is deploying colossal human and financial resources. The company has recruited several strategic talent from competing companies. Among them, Alexandr Wang, former CEO of Scale AI, will head the new lab, alongside Nat Friedman, former CEO of GitHub, who will oversee product direction and open source model strategy. This leadership team, with extensive experience in AI, will structure all advanced research projects and lead the integration of superintelligence models into Meta products. At the same time, Meta has been conducting an aggressive recruitment campaign for several weeks, targeting talent from Google DeepMind, OpenAI, and Anthropic. According to several sources, nearly a dozen engineers and researchers who contributed to the development of GPT-4 and Claude have already joined the lab. This direct competition between technology giants heralds a fierce war for talent, where Meta does not hesitate to offer exceptional compensation packages of up to $100 million for the best profiles. Record investments to support this ambition Beyond human resources, Meta is investing massively to support its ambitions in the field of artificial intelligence. In 2025, the company plans to spend between $65 and $70 billion expanding its computing infrastructure, developing new data centers, and purchasing specialized GPU clusters for training very large-scale models. Meta also announced that it has acquired a 49% stake in Scale AI, consolidating its capabilities in processing and annotating critical data for AI training. These financial resources aim to position Meta at the forefront of AI research, capable of competing with OpenAI, Google, and Anthropic, which are also accelerating the deployment of increasingly powerful models. With his Meta Superintelligence Labs, Zuckerberg aims to create multimodal models that would work not only on his social applications, but also in industrial, robotic, and immersive environments. A strategy based on multimodal AI and superintelligence The core of Meta's strategy is based on the development of multimodal models capable of understanding and producing content in different forms: text, images, videos, voice, and environmental signals. The idea is to offer integrated, autonomous, and customizable artificial intelligence that could be deployed both in Meta applications (Facebook, Instagram, WhatsApp) and in professional or healthcare use cases. The company also aims to reach the stage of superintelligence: general-purpose AI surpassing human cognitive abilities on a wide range of tasks. This level of artificial intelligence, which is still a matter of debate in the scientific community, represents the technological horizon that Meta hopes to achieve within the next five years. The Menlo Park-based firm is increasing its scientific publications and technical demonstrations around its Llama 4.1 model, while announcing the advanced development of Llama 4.2, planned for early 2026. Ethical Issues and Industrial Challenges However, this strategy poses numerous challenges, both technically and ethically and regulatoryly. Meta will need to ensure it manages the biases, reliability, and societal impact of its systems, as increasingly autonomous AI raises questions of liability, data protection, and algorithmic transparency. The company will also need to manage the organizational complexity of integrating its new teams and coordinating international projects spread across California, Austin, and Europe. Faced with growing concerns about generative AI, Meta is also committed to publishing some of its work as open source and collaborating with academic researchers to ensure the security and robustness of its models. The company thus intends to reconcile technological innovation and social acceptability to remain a key player in a rapidly evolving sector. With the launch of Meta Superintelligence Labs ... .... Zuckerberg clearly asserts his ambition to gain a head start in the global race for artificial intelligence. By leveraging unprecedented human, financial, and technological resources, and focusing its efforts on superintelligent and multimodal AI, Meta intends to establish itself as the driving force behind the next generation of universal intelligent assistants and systems. This initiative confirms that the competition for control of tomorrow's AI is now being played out at the scale of super-labs and specialized cloud platforms. Meta, with its infrastructure, ecosystem, and open-source models under development, could well upset the established balance in the coming months. Sources: CNBC — Zuckerberg memo on Meta Superintelligence Labs : https://tinyurl.com/CNBCmemo Houston Chronicle — Meta AI Labs opening : https://tinyurl.com/houstonChro

Modern JavaScript projects rely on an ever-growing list of dependencies. While tools like NPM and Yarn are essential for managing these dependencies, they can quickly lead developers into what is known as “dependency hell.” This term refers to issues like version conflicts, missing or outdated packages, and install errors—all of which can cripple a project. Understanding Common Dependency Issues Among the most frequent challenges are version conflicts. These occur when different packages require incompatible versions of the same dependency. There are also peer dependency issues, outdated libraries, and missing packages that are not listed in `package.json`. Additionally, circular dependencies can create unnecessary complexity. If left unresolved, these problems can stall development. They may turn a healthy codebase into a technical mess. It is essential to identify these challenges early to keep your project on track. Quick Fixes: Commands and Immediate Solutions Several quick actions can help troubleshoot dependency issues:

Small and medium-sized enterprises (SMEs) are often perceived as lower-priority targets than large corporations, which is a dangerous misconception. In reality, SMEs are particularly vulnerable to cyberattacks due to limited resources, sometimes insufficient awareness, and less robust defense systems. A cyberattack can result in significant financial losses, business interruption, loss of sensitive data, and irreparable damage to the company's reputation. Securing your business is no longer an option; it's an imperative to ensure its long-term viability. You can also serve as an attack vector against your customers! Understanding the Specific Threats to SMEs SMEs face a similar range of digital threats to large enterprises, but with potentially more devastating consequences due to their reduced ability to absorb shocks. The most common threats include: Phishing and social engineering: Attacks that manipulate employees into disclosing confidential information or clicking on malicious links. Ransomware: Malicious software that encrypts company data and demands a ransom to unlock it. Malware: Software designed to damage or disable computer systems, steal data, or disrupt operations.

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Data Architect Status: Status Saved for later Like Job ID: JOB-1752154156901 Location: Geneva Employment type: Permanent contract (100%) Company type: Corporate Work setup: Hybrid Compensation model: Salary Job duration: Permanent Skills required: Close Close Link copied about the position We’re looking for an experienced and visionary Data Architect to join our growing Data team and help shape the future of our data ecosystem. In this role, you’ll be responsible for designing, governing, and evolving data architectures across key business domains within the Group. As a central figure between the Data Office, IT, and business units, you will provide expert guidance, promote data standards, and drive the adoption of modern data technologies aligned with business strategy and regulatory frameworks. key responsibilities What You'll Do Design, implement, and maintain an enterprise data architecture framework that supports both operational and regulatory requirements. Define scalable, efficient, and future-ready data architectures in collaboration with engineering and business stakeholders. Establish and enforce data architecture standards, policies, and best practices within assigned data domains. Provide expert advice on data modeling, data integration patterns, and architectural decisions. Support data owners and custodians throughout the data lifecycle, ensuring full traceability, compliance, and data quality. Contribute to data governance committees and architecture boards to advocate for sustainable, value-driven data practices. Stay ahead of market trends, emerging technologies, and regulatory evolutions, proactively recommending strategic adjustments. hard skills required skills description Your Profile Degree in Computer Science, Data Science, Information Systems, or a related discipline. At least 8 years of experience in data architecture, data engineering, or similar positions. Proven track record of leading data transformation and innovation initiatives within complex, large-scale organizations. Solid understanding of regulatory frameworks and compliance challenges in the Financial Services sector. Strong expertise in modern data architectures including data lakes, data warehouses, event-driven models, microservices, and data mesh. In-depth experience with ETL/ELT processes, data lifecycle management, data governance, compliance, and security. Excellent awareness of market trends, and established contacts within the tech ecosystem (vendors, hosting providers, cloud solutions). Strong analytical skills combined with the ability to engage and influence both C-level executives and operational teams. about the company Ready to shape the future of data with us? Apply now and join a team where your expertise will drive real business impact. sign up to apply job board apply now apply now apply now job board *IMPORTANT NOTE: For freelancing and wage portage contracts, we only work with verified professionals and companies. Clicking "Apply now" will take you to the secure GYFF platform, where you must create a registered professional account. This account, included in your Hapidev membership , confirms your legal employability by verifying your tax and business registration. Only members with a completed GYFF profile can be selected, hired, and paid for projects in a secure environment—for both you and the employer. learn more other competences (nice to have)