Financial Data and Key Metrics Changes - In Q4 2025, revenue increased by 5% year-over-year to a record $1.22 billion, while full-year revenue grew by 4% to $4.48 billion, hitting the upper end of guidance [5][6] - Adjusted EBITDA for Q4 was $88.7 million, a record for the company, with a full-year adjusted EBITDA of $323.3 million and a margin of 7.2% [6][15] - Adjusted net income for Q4 was $49.3 million, representing a 16% increase year-over-year, while full-year adjusted net income was $166.8 million, a 20% increase [6][17] - The company improved its net debt by $116 million year-over-year, resulting in a net leverage ratio of 2.2 times [7][18] Business Line Data and Key Metrics Changes - Growth was primarily driven by training, Foreign Military Sales, and rapid prototyping programs [15] - The company secured two contracts valued at over $1 billion each and ten awards exceeding $100 million, reflecting strong customer relationships and execution capabilities [8][10] Market Data and Key Metrics Changes - The qualified pipeline stands at over $60 billion, with a 50% increase in bid velocity in 2025 and a targeted additional 30% increase in 2026 [10] - The Indo-Pacific market showed flat to slightly down performance, with expectations for improvement in 2026 [43] Company Strategy and Development Direction - The company is focused on leading with innovation, prioritizing investments and partnerships to deliver solutions that meet customer requirements [4][12] - Partnerships with Amazon Web Services and Google Public Sector aim to enhance capabilities in smart warehousing and AI solutions [12][63] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the company's momentum exiting 2025 and its ability to deliver enhanced value for customers and shareholders in 2026 [5][10] - The company anticipates revenue growth of 6% in 2026, with adjusted EBITDA estimated at $335 million to $350 million [20][22] Other Important Information - The backlog at the end of 2025 was $11.1 billion, with funded backlog slightly improving to $2.3 billion [19] - The T-6 contract is expected to contribute approximately $140 million to $160 million in revenue for 2026 [32] Q&A Session Summary Question: What has been the trajectory of the company's revenue and activity in the Middle East region? - Management noted the situation is fluid, prioritizing employee safety, and will adapt as circumstances evolve [27][28] Question: How much contribution do you expect from the T-6 contract? - The T-6 contract is expected to generate around $140 million to $160 million in revenue for the year [32] Question: What is the status of the remaining $1 billion opportunities? - Two opportunities have been awarded, and the remaining three are awaiting adjudication, with positive expectations [38][40] Question: Any updates on the Indo-Pacific market? - The market has been flat to slightly down, with hopes for improvement in 2026 [43] Question: How do you see AI partnerships impacting the company? - Partnerships with AWS and Google are expected to enhance operational efficiency and customer outcomes through advanced technology [63][75]

I just love building things. You know, I was one of those kids that just was always taking things apart. And then I quickly kind of realized that you can do that to help people.The power of good design is you can transform the world and you can transform other people's lives for the better. Using Gemini and deep think mode, we're now able to design and iterate faster than ever before. This is one of the products that we had when we were a startup.This was designed for people with cerebopaly or spinal cord i ...

I just love building things. You know, I was one of those kids that just was always taking things apart. And then I quickly kind of realized that you can do that to help people.The power of good design is you can transform the world and you can transform other people's lives for the better. Using Gemini and deep think mode, we're now able to design and iterate faster than ever before. This is one of the products that we had when we were a startup.This was designed for people with cerebopaly or spinal cord i ...

AI Engine Rapid Prototyping Overview - AMD introduces the Versal AI Engine Rapid Prototyping using the AMD Vitis Unified IDE for early design analysis and risk reduction [1][2][12][13] - The rapid prototyping feature is available in the Vitis Unified IDE in version 20242 [13][16] Key Steps in Rapid Prototyping - Involves resource estimation, including tile count, buffer usage, PLIO resources, and stream array traffic [2] - Assesses latency and throughput feasibility with early data flow simulations, prototype kernel coding, and initiation interval loop analysis [2] - Utilizes Vitis libraries for existing block elements and develops candidate vectorization options [3] - Includes building empty kernel wrappers, building the graph and compiling, simulating and analyzing for early estimation [12] Custom Kernel Example: Digital Up Conversion (DUC) Chain - The DUC chain translates a signal from baseband to intermediate frequency band and includes a FIR fractional resampler, half-band interpolators, DDS mixer functions, and an adder functional block [5] - The FIR fractional resampler, the half-band interpolators, and DDS mixer functions can be implemented using the Vitis DSP Library [5] - Focuses on fast prototyping of the custom adder kernel, identifying input/output data types, coefficient types, number of taps, sampling rate, and the kernel function [6] AI Engine System Mapping - Identifies hardware resources such as the number of AI Engine tiles, storage, buffers, and connectivity ports [8] - Considers compute (AIE tiles), storage (buffer size, local memory, DMA size), and input/output bandwidth (PLIO ports, clocking, buffer/stream interfaces) [8] - A custom adder kernel requires a sampling rate of 1200 MSPS with a latency less than 500 ns [9] - The adder is implemented in one tile with two inputs and one output of cint16 type, taking 3KB of data at a sampling rate of 1200 MSPS [10][11] Vitis Unified IDE Implementation - Generates data flow models with parametrized kernel ports, multi-core graph topology, full buffering, stream details, and LUT storages [14] - Allows exploration of hardware utilization through AI Engine compilation and ensures throughput and latency requirements are met through AI engine emulation [14] - Requires creating a new empty AI engine component and using the "Generate AIE Prototype Code" option [15] - Involves setting kernel properties such as name, input/output port properties (data type cint16, dimension to 384 samples), and enabling "Generate Top Level graph and Simulation code" [19][20] Simulation and Analysis - The tool generates graph CPP and H files, with the graph CPP setting the graph to run for one iteration (modifiable for better analysis) [20][21] - Requires adding input text files for simulation, containing values representing cint16 samples per clock on the 64-bit interface [22][23][24][25] - Simulation results report a throughput of 5000 megabytes/second or 1250 mega 16-bit complex samples per system, meeting the requirements [26]