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 山谷怪胎

山谷怪胎

风险投资与私募股权管理人

What started off as a coffee chat has now grown into a platform featuring: CEOs, Venture Capitalists and Visionaries.

关于我们

“山谷极客”与当今引领各自行业的全球最聪明的人联系在一起,讨论即将到来的最热门行业趋势以及他们的工作如何影响全球经济。

网站
https://geeksofthevalley.com
所属行业
风险投资与私募股权管理人
规模
2-10 人
总部
Silicon Valley
类型
私人持股
创立
2019
领域
Blockchain、B2C、B2B2C、B2B、Biotech、Internet of Things、Enterprise、Adtech、Ecommerce、Healthtech、Social Networks、BigData、Machine Learning、SaaS、Life Sciences、Manufacturing、Mobile、Podcasts、Trends、Technology、Fintech、Venture Capital & Private Equity和Entrepreneurship

地点

山谷怪胎员工

动态

  • 山谷怪胎转发了

    查看Kunal T.的档案

    Venture Capital & Private Equity

    PwC Ventures and Corporate Finance is pleased to announce our role as exclusive financial advisor to RedotPay a leading crypto payments platform, on its $40 million Series A financing led by Lightspeed with significant investments from HSG and Galaxy Ventures. The round also saw participation from DST Global, Accel, Vertex Ventures SE Asia & India (Temasek-backed VC), among other investors. Founded in April 2023, RedotPay quickly established itself as a pioneering alternative to traditional banking for the unbanked. With over 3 million registered users globally, the industry leading crypto card & payment platform’s rapid adoption underscores the growing demand for crypto-based payment solutions in everyday transactions. ? This transaction highlights PwC Ventures' emerging technology domain expertise, as well as our extensive track record advising companies in the space. ? Learn more about us here: https://lnkd.in/gtetBUng #innovation #entrepreneurship #venturecapital #technology #investing

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    4,136 位关注者

    Semiconductors are the critical enablers behind nearly every major advancement in AI, autonomous systems, and high-performance computing (HPC). In 2024, breakthroughs in chip design, workload optimization, and next-generation materials are driving a new era of computational efficiency and scalability. ?? Advancements in HPC: ? Silicon photonics (e.g., Intel’s co-packaged optics) is revolutionizing data transfer with near-light-speed transmission, significantly reducing latency for AI and ML workloads. ? Memory stacking (e.g., HBM integration in NVIDIA GPUs) enhances bandwidth and data access speed, optimizing performance for compute-intensive applications. ? Chiplets, a modular alternative to monolithic chips, improve scalability and cost efficiency, overcoming the limitations of traditional semiconductor design. ?? The Rise of Custom & Modular Architectures: ? AI/ML-specific processors (e.g., Google’s TPUs, Hailo’s NPUs, and Cerebras’ wafer-scale engines) are purpose-built to enhance model training and inference efficiency. ? Custom ASICs and FPGAs provide highly specialized processing capabilities, balancing performance, energy efficiency, and flexibility. ? Chiplet-based architectures allow greater modularity and integration, paving the way for more efficient, scalable semiconductor solutions. ?? The Evolving Compute Landscape: ? Data centers (e.g., CoreWeave, Lambda) remain critical for large-scale batch processing and analytics. ? Edge computing (e.g., Vapor IO, Mutable) brings processing closer to users, enabling low-latency AI applications and IoT connectivity. ? Hybrid compute models are seamlessly balancing workloads between centralized and distributed systems, optimizing efficiency and performance across environments.

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    ?? Fintech Resilience: What to Expect in 2025 After a tough period in 2022, the fintech industry has proven its resilience, with many companies scaling significantly. The focus is shifting from rapid growth at all costs to building sustainable business models. As the IPO market reopens and investors seek capital-efficient growth, 2025 is poised to be a defining year for fintech. ?? Here’s a snapshot of key trends shaping the sector: ? ?? Strong Performance: The F-Prime Fintech Index has seen substantial growth, outperforming traditional markets and reaching a market cap of $573 billion by the end of 2023. ? ?? Sustainable Growth: Fintech companies are moving away from the unsustainable growth patterns of previous years, instead focusing on profitability and long-term sustainability. ? ?? Revenue Growth: Over the past two years, fintech revenues have increased by 14% globally, with a 21% growth rate in markets excluding crypto. ? ?? Profitability: Many fintech companies are now profitable, collectively contributing significant profits, a shift from the earlier years of high cash burn. ? ?? Valuation Multiples: Fintech valuations have stabilized at 5.6x in Q4 2024, down from the speculative 20x+ multiples seen in 2021, signaling a more disciplined market. ? ?? Investor Sentiment: Investors are now favoring companies that strike a balance between growth and profitability, rewarding those that show long-term viability rather than unsustainable growth. The recovery and evolution of fintech is a testament to the sector’s resilience and the shift towards smarter, more efficient growth. As the market matures, the opportunities are ripe for those focused on creating lasting value.

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    4,136 位关注者

    In most industries, software companies come and go, with new players using technology to disrupt the old guard. Cloud computing, for instance, made it easy for startups to build tools without needing massive resources. Almost every software category has seen challengers rise and take over. But one industry has resisted this wave of disruption: physical design software—tools like CAD, EDA, and simulation software. Unlike other software sectors, the leaders in this space—Autodesk, Dassault, Synopsys, and others—are more powerful than ever. Their dominance seems unshakable, but why is that? The answer lies in the complexity of their tools. Building physical design software requires years of development and expertise. Companies that rely on these tools face high risks if they switch, like retraining employees or encountering costly errors in their designs. As a result, most businesses stick with what they know, and the big players stay firmly in control. This dominance has deep roots. Back in the 1950s and 1960s, companies like Renault (which eventually became Dassault) created the first computer-aided design (CAD) systems. By the 1980s, modern design software emerged, with companies like Autodesk and Cadence offering affordable, PC-based solutions. These tools became the standard, and the big players grew even stronger through acquisitions and expanding their offerings. For decades, the industry has been a fortress, but cracks are starting to appear. A new wave of innovation is reshaping what’s possible. ? Generative AI is enabling tools that can design and optimize parts automatically. ? Advanced simulations powered by AI are making real-world testing faster and more accurate. ? Smarter manufacturing tools are helping companies ensure their designs can actually be built efficiently. ? Automation is streamlining repetitive tasks like quality checks and design assessments. These changes hint at a future where designing complex systems becomes faster, cheaper, and more accessible. Startups are beginning to explore opportunities in these areas, but they face an uphill battle against the deeply entrenched incumbents. The question now is: will these new technologies be enough to disrupt the industry, or will the big players adapt and maintain their dominance? What’s clear is that physical design software is at the start of a new chapter. The tools that shape the products we use every day—cars, electronics, buildings—are evolving, and the next wave of innovation could transform how engineers work and what they can achieve. For now, the incumbents hold the keys, but the future may bring surprising twists to this long-standing tale of dominance. https://lnkd.in/gtQFtA9N

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    4,136 位关注者

    For decades, businesses followed a simple equation: labor first, technology second. AI is reversing that equation—not by optimizing tasks, but by automating decision-making itself. ?? The shift is already in motion: ? OpenAI’s 10x price hike signals AI demand is skyrocketing. ? AI-first startups are hitting $20M revenue in months with lean teams. ? Companies have cut customer service staff by 70%, shifting costs to AI-driven systems. ? Microsoft’s $80B investment in AI infrastructure confirms this is no short-term trend. Unlike past tech shifts that needed factories or retraining, AI slots into existing workflows instantly. Three forces are accelerating adoption: ? ? Digital-first work – No infrastructure overhaul needed. ? ? AI scalability – Models fine-tune in hours, not months. ? ? Compute-driven intelligence – AI scales with compute, not headcount, making energy the real bottleneck. ?? What This Means for Businesses: ? ?? AI-native companies are proving 8-figure revenues are possible with teams under 20. ? ? Compute budgets will surge 5-10x per quarter as AI replaces human decision-making. ? ?? Traditional metrics like revenue per employee are becoming obsolete as AI scales autonomously

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