DoD awards $5.9M R&D contract for deep transfer learning to Matrix Research Inc

Contract Overview

Contract Amount: $5,932,583 ($5.9M)

Contractor: Matrix Research Inc

Awarding Agency: Department of Defense

Start Date: 2020-07-31

End Date: 2027-12-31

Contract Duration: 2,709 days

Daily Burn Rate: $2.2K/day

Competition Type: FULL AND OPEN COMPETITION

Number of Offers Received: 1

Pricing Type: COST PLUS FIXED FEE

Sector: R&D

Official Description: DEEP TRANSFER LEARNING

Place of Performance

Location: BEAVERCREEK, GREENE County, OHIO, 45430

State: Ohio Government Spending

Plain-Language Summary

Department of Defense obligated $5.9 million to MATRIX RESEARCH INC for work described as: DEEP TRANSFER LEARNING Key points: 1. Contract focuses on advanced research and development in physical, engineering, and life sciences. 2. Matrix Research Inc. secured this definitive contract through full and open competition. 3. The contract duration spans over 7 years, indicating a long-term research objective. 4. Performance is located in Ohio, suggesting regional economic impact. 5. The cost-plus-fixed-fee structure incentivizes efficient cost management by the contractor. 6. This award falls under the broad category of R&D in physical and engineering sciences.

Value Assessment

Rating: fair

The contract value of $5.9 million over approximately 7 years suggests a moderate investment in specialized R&D. Without specific deliverables or milestones, a direct value-for-money assessment is challenging. Benchmarking against similar R&D contracts in deep transfer learning is difficult due to the specialized nature of the work and limited public data on comparable projects. The cost-plus-fixed-fee (CPFF) pricing structure is common for R&D where scope can evolve, but it requires careful oversight to ensure costs remain reasonable.

Cost Per Unit: N/A

Competition Analysis

Competition Level: full-and-open

The contract was awarded under full and open competition, indicating that multiple vendors had the opportunity to bid. This competitive process is generally expected to yield fair pricing and innovative solutions. The number of bidders is not specified, but the open competition suggests a healthy market for these specialized R&D services.

Taxpayer Impact: Taxpayers benefit from the potential for competitive pricing and the selection of the most capable contractor through an open bidding process.

Public Impact

Advances in deep transfer learning capabilities for potential defense applications. Supports research and development activities within the physical, engineering, and life sciences sectors. Potential for technological advancements that could enhance national security or scientific understanding. Economic impact in Ohio through research-focused employment and resource utilization.

Waste & Efficiency Indicators

Waste Risk Score: 50 / 10

Warning Flags

The long contract duration (over 7 years) could lead to cost overruns if not managed effectively.
CPFF contracts can incentivize spending if not closely monitored for efficiency.
The specialized nature of deep transfer learning may limit the pool of qualified oversight personnel.

Positive Signals

Awarded through full and open competition, suggesting a robust selection process.
Focus on R&D aligns with strategic technological advancement goals.
Matrix Research Inc. is likely selected based on demonstrated expertise in the field.

Sector Analysis

This contract falls within the Research and Development sector, specifically focusing on advanced computational techniques like deep transfer learning. The market for such specialized AI/ML R&D is growing rapidly, driven by both commercial and government demand. Comparable spending benchmarks are difficult to establish due to the niche nature of the technology, but significant investment is being made across various agencies in AI and machine learning capabilities.

Small Business Impact

The contract was awarded under full and open competition and does not indicate any specific small business set-aside. There is no information provided regarding subcontracting plans for small businesses. Therefore, the direct impact on the small business ecosystem from this specific award is likely minimal unless Matrix Research Inc. voluntarily engages small businesses as subcontractors.

Oversight & Accountability

Oversight for this contract will likely be managed by the Department of the Air Force, a component of the Department of Defense. As a Cost Plus Fixed Fee contract, rigorous financial oversight and performance monitoring are crucial to ensure adherence to the research objectives and cost containment. The contract's long duration necessitates sustained oversight to track progress and manage risks effectively. Transparency will depend on the DoD's reporting practices for R&D contracts.

Related Government Programs

Department of Defense Research and Development Programs
Artificial Intelligence and Machine Learning Initiatives
Advanced Computing Research Contracts
Deep Learning and Transfer Learning Research

Risk Flags

Long contract duration may increase risk of cost overruns or changing priorities.
CPFF structure requires diligent oversight to ensure cost efficiency.
Specialized R&D area may limit available expertise for oversight.

Frequently Asked Questions

What is this federal contract paying for?

Department of Defense awarded $5.9 million to MATRIX RESEARCH INC. DEEP TRANSFER LEARNING

Who is the contractor on this award?

The obligated recipient is MATRIX RESEARCH INC.

Which agency awarded this contract?

Awarding agency: Department of Defense (Department of the Air Force).

What is the total obligated amount?

The obligated amount is $5.9 million.

What is the period of performance?

Start: 2020-07-31. End: 2027-12-31.

What is Matrix Research Inc.'s track record with government R&D contracts, particularly in AI/ML?

Information regarding Matrix Research Inc.'s specific track record with government R&D contracts, especially in the niche area of AI/ML and deep transfer learning, is not readily available in the provided data. A comprehensive assessment would require reviewing their past performance on similar contracts, including successful project completion, adherence to budget, and technical innovation. Government contract databases and performance reports (if publicly accessible) would be the primary sources for evaluating their expertise and reliability in this specialized field. Without this historical data, it's difficult to definitively assess their capabilities beyond the current award.

How does the $5.9 million value compare to similar deep transfer learning R&D contracts?

Benchmarking the $5.9 million value against similar deep transfer learning R&D contracts is challenging due to the specialized and evolving nature of this field. Publicly available data on specific deep transfer learning R&D contracts, especially those funded by the Department of Defense, is often limited. However, R&D contracts in advanced AI and machine learning can range significantly in value, from smaller, focused projects to multi-year, multi-million dollar initiatives. The value of this contract appears moderate for a long-term R&D effort in a cutting-edge technological area, suggesting a focused scope rather than a broad, foundational research program.

What are the primary risks associated with a 7-year Cost Plus Fixed Fee R&D contract?

The primary risks associated with a 7-year Cost Plus Fixed Fee (CPFF) R&D contract include potential cost overruns if the contractor's expenses exceed initial estimates, although the fixed fee provides a ceiling on profit. Scope creep is another significant risk, where the research objectives may expand beyond the original intent, leading to increased costs and extended timelines. Contractor performance risk is also present; the contractor might fail to achieve the desired technical breakthroughs or deliver the expected outcomes within the allocated timeframe. Furthermore, the long duration increases the risk of technological obsolescence or shifts in research priorities, potentially rendering the project's outcomes less relevant by its completion.

What specific deliverables or milestones are expected under this contract?

The provided data does not specify the exact deliverables or milestones for this contract. Deep transfer learning R&D contracts typically involve the development of algorithms, models, software prototypes, research reports, and potentially demonstrations of technology capabilities. Given the 7-year duration and CPFF structure, the deliverables are likely to be phased, with interim reports and prototypes leading to a final research outcome. The specific nature of these deliverables would be detailed in the contract's statement of work (SOW), which is not included in the provided summary data.

How does this contract align with the Department of Defense's broader AI/ML strategy?

This contract aligns with the Department of Defense's (DoD) broader strategy to leverage artificial intelligence (AI) and machine learning (ML) for enhanced capabilities. Deep transfer learning is a key area within AI/ML that allows models trained on one task to be adapted for different, related tasks, potentially accelerating development and improving performance in areas like image recognition, natural language processing, and predictive analytics. By investing in this R&D, the DoD aims to develop advanced technologies that can provide a strategic advantage, improve decision-making, and enhance operational effectiveness across various defense domains.

What is the significance of the 'Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)' NAICS code?

The NAICS code 541715, 'Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology),' signifies that this contract is focused on fundamental and applied research across a broad spectrum of scientific and technical disciplines. This includes areas like advanced materials, energy, environmental science, computer science (excluding specific subfields like nano/biotech), and various engineering disciplines. Awarding a contract under this code indicates the government's intent to fund cutting-edge scientific inquiry and technological innovation that could have broad applications, potentially leading to future breakthroughs and advancements in defense and other sectors.

Industry Classification

NAICS: Professional, Scientific, and Technical Services › Scientific Research and Development Services › Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)

Product/Service Code: RESEARCH AND DEVELOPMENT › C – National Defense R&D Services

Competition & Pricing

Extent Competed: FULL AND OPEN COMPETITION

Solicitation Procedures: NEGOTIATED PROPOSAL/QUOTE

Solicitation ID: FA865019S1943

Offers Received: 1

Pricing Type: COST PLUS FIXED FEE (U)

Evaluated Preference: NONE

Contractor Details

Address: 3844 RESEARCH BOULEVARD, DAYTON, OH, 45430

Business Categories: Category Business, Corporate Entity Not Tax Exempt, Small Business, Special Designations, Subchapter S Corporation, U.S.-Owned Business

Financial Breakdown

Contract Ceiling: $8,294,817

Exercised Options: $8,294,817

Current Obligation: $5,932,583

Actual Outlays: $28,774

Contract Characteristics

Commercial Item: COMMERCIAL PRODUCTS/SERVICES PROCEDURES NOT USED

Cost or Pricing Data: NO

Timeline