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Gaps In The AI Debug Process


When an AI algorithm is deployed in the field and gives an unexpected result, it's often not clear whether that result is correct. So what happened? Was it wrong? And if so, what caused the error? These are often not simple questions to answer. Moreover, as with all verification problems, the only way to get to the root cause is to break the problem down into manageable pieces. The semico... » read more

Improving Accuracy In Satellite Navigation Systems


Increasing dependency on the global navigation satellite system (GNSS) constellations is raising concerns about what happens when signals are unavailable, even for short periods of time. GNSS systems affect our daily lives in ways we often don’t see, from location services to cell phone timing. In fact, these satellites have become a necessary part of critical infrastructure, and higher ac... » read more

Roadblocks For ML in EDA


Is EDA a suitable space for utilizing machine learning (ML)? The answer depends on a number of factors, including where exactly it is being applied, how much support there is from the industry, and whether there are demonstrable advantages. Exactly where ML will play a role has yet to be decided. Replacing existing heuristics with machine learning, for example, would require an industry-wide... » read more

How To Measure ML Model Accuracy


Machine learning (ML) is about making predictions about new data based on old data. The quality of any machine-learning algorithm is ultimately determined by the quality of those predictions. However, there is no one universal way to measure that quality across all ML applications, and that has broad implications for the value and usefulness of machine learning. “Every industry, every d... » read more

Hidden Costs In Faster, Low-Power AI Systems


Chipmakers are building orders of magnitude better performance and energy efficiency into smart devices, but to achieve those goals they also are making tradeoffs that will have far-reaching, long-lasting, and in some cases unknown impacts. Much of this activity is a direct result of pushing intelligence out to the edge, where it is needed to process, sort, and manage massive increases in da... » read more

Neural Networks Without Matrix Math


The challenge of speeding up AI systems typically means adding more processing elements and pruning the algorithms, but those approaches aren't the only path forward. Almost all commercial machine learning applications depend on artificial neural networks, which are trained using large datasets with a back-propagation algorithm. The network first analyzes a training example, typically assign... » read more

Bridging Math And Engineering In ML


Steve Roddy, vice president of products for Arm’s Machine Learning Group, examines the intersection of high-level mathematics in the data science used in machine learning within area, speed, and power limitations, and how to bring these two worlds together with the least amount of disruption. » read more

The Cost Of Accuracy


How accurate does a system need to be, and what are you willing to pay for that accuracy? There are many sources of inaccuracy throughout the development flow of electronic systems, most of which involve complex tradeoffs. Inaccuracy leaves an impact on your design in ways you are not even aware of, hidden by best practices or guard-banding. EDA tools also inject some inaccuracy. As the i... » read more

How Good Is 95% Accuracy?


Conventional, deterministic computers don’t make mistakes. They execute a predictable series of computations in response to any given input. The input might be mistaken. The logic behind the operations that are performed might be flawed. But the computer will always do exactly what it has been told to do. When unexpected results occur, they can be attributed to the programmer, the system manu... » read more

Power Modeling And Analysis


Semiconductor Engineering sat down to discuss power modeling and analysis with [getperson id="11489" p_name="Drew Wingard"], CTO at [getentity id="22605" e_name="Sonics"]; [getperson id="11763" comment="Tobias Bjerregaard"], CEO at [getentity id="22908" e_name="Teklatech"]; Vic Kulkarni, vice president and chief strategy officer at [getentity id="22021" e_name="Ansys"]; Andy Ladd, CEO of Baum; ... » read more

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