Core Viewpoint - The speed of training large AI models ultimately depends on two concepts: scaling up and scaling out, which involve different physical connection technologies [1][2]. Group 1: Scaling Technologies - Scaling out refers to increasing the number of interconnected AI computers to handle large tasks, while scaling up involves integrating as many GPUs as possible within each computer [1]. - Scaling out relies on photonic chips and optical fibers for data transmission, while scaling up uses copper cables, which are simpler and more economical [1]. - The network density achieved through scaling up is approximately ten times that of scaling out, but the data transfer rates required for high-performance computing are approaching the physical limits of copper cables [1][2]. Group 2: Challenges with Copper Cables - Copper cables face limitations due to the skin effect, which causes high-frequency signals to concentrate near the surface, increasing resistance and requiring thicker cables and more power [7][8]. - Active electrical cables (AECs) have been developed to mitigate these issues, but they increase complexity and power consumption [8]. Group 3: Innovations in Data Transmission - Point2 Technology and AttoTude propose a new solution that combines the low cost and reliability of copper cables with the fine size and long-distance capabilities of optical fibers [2][4]. - Point2 plans to mass-produce cables capable of 1.6 terabits per second using polymer waveguides, while AttoTude is developing similar technology using terahertz frequencies [4][11]. - Both companies claim their technologies can easily surpass copper cables in transmission distance, achieving 10-20 meters without significant loss [4][5]. Group 4: Future Prospects - The wireless technology being developed is expected to be more reliable and easier to manufacture than photonic technology, potentially replacing some copper cables in printed circuit boards [5][14]. - The market for vertical expansion networks is growing, with companies looking to integrate more GPUs while minimizing cooling technology needs [15][16]. - Both Point2 and AttoTude are working on versions of their technology that can be directly integrated into GPUs, which could further enhance performance and efficiency [15][16].

Core Insights - Credo has reported exceptional Q1 results for FY2026, with revenue soaring 274% year-over-year to $223.1 million, and adjusted earnings per share of $0.52, significantly exceeding market expectations [1][3] - Following the impressive earnings report and strong guidance, Credo's stock surged nearly 13% in after-hours trading, and the stock has risen approximately 85% year-to-date, outperforming the Nasdaq Composite's 11% increase during the same period [1][3] Financial Performance - Credo's revenue and profit have greatly surpassed Wall Street expectations, with adjusted earnings per share at $0.52 compared to the analyst forecast of $0.36, and revenue reaching $223.1 million, exceeding the consensus estimate of $190.6 million [3] - The company anticipates continued strong growth, with a sales guidance midpoint of $235 million for the current quarter, well above the analyst consensus of $201.9 million [3] Strategic Positioning - Credo's growth is attributed to deep strategic partnerships with major data center operators and key clients, driven by increasing demand for reliable and efficient connectivity solutions [3] - The company is developing system-level optical connectivity solutions aimed at providing higher reliability and energy efficiency for its customers [3] Market Leadership - Credo plays a critical role in high-speed data connectivity for AI data centers, offering various products, with a focus on Active Electrical Cables (AECs) [4][5] - The company holds a dominant position in the AEC market, with a 73% market share as of the last reporting quarter, and the demand for AECs is expected to rise significantly as the market shifts towards higher GPU density rack servers [5] - Major tech giants such as Amazon, Microsoft, and xAI are key customers of Credo, reflecting strong demand driven by substantial investments in AI infrastructure [5]