Evaluation - Revision history

BPeat at 03:09, 6 December 2023

2023-12-06T03:09:14Z

BPeat at 23:12, 3 September 2023

2023-09-03T23:12:44Z

BPeat at 16:10, 9 July 2023

2023-07-09T16:10:16Z

BPeat at 16:33, 30 June 2023

2023-06-30T16:33:13Z

BPeat at 16:32, 30 June 2023

2023-06-30T16:32:04Z

BPeat at 16:31, 30 June 2023

2023-06-30T16:31:34Z

BPeat at 16:29, 30 June 2023

2023-06-30T16:29:57Z

BPeat at 20:00, 17 June 2023

2023-06-17T20:00:11Z

BPeat at 13:34, 21 May 2023

2023-05-21T13:34:16Z

BPeat at 01:08, 18 May 2023

2023-05-18T01:08:43Z

@@ Line 98: / Line 98: @@
 * Does [[AI Governance]] implement a risk-based approach, e.g. greater consideration or controls for high risk use cases?
 * What are the [[Enterprise Architecture (EA)|AI architecture]] specifics, e.g. [[Ensemble Learning]] methods used, [[Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning]], [[Digital Twin]],  [[Decentralized: Federated & Distributed]]?
-* Is the [[Neuroscience|wetware/brain]] or hardware involved, e.g. [[Internet of Things (IoT)]]; [[Signal Processing|physical sensors]], [[Javascript|mobile phones]], [[Screening; Passenger, Luggage, & Cargo|screening devices]], [[Vision|cameras/surveillance]], [[Healthcare|medical instrumentation]], [[Robotics|robots]], [[Transportation (Autonomous Vehicles)|autonomous vehicles]], [[Autonomous Drones|drones]], [[Quantum|quantum computing]], [[Assistants|assistants/chatbots]]?
+* Is the [[Neuroscience|wetware/brain]] or hardware involved, e.g. [[Internet of Things (IoT)]]; [[Signal Processing|physical sensors]], [[JavaScript|mobile phones]], [[Screening; Passenger, Luggage, & Cargo|screening devices]], [[Vision|cameras/surveillance]], [[Healthcare|medical instrumentation]], [[Robotics|robots]], [[Transportation (Autonomous Vehicles)|autonomous vehicles]], [[Autonomous Drones|drones]], [[Quantum|quantum computing]], [[Assistants|assistants/chatbots]]?
 * What [[Learning Techniques|learning technique(s) are or will be implemented?]] If a [[Transfer Learning| a transfer process]] is used, which model(s) and what mission specific [[Datasets|dataset(s)]] are used to tune the AI model?
 * What [[PRIMO.ai#Algorithms|AI algorithms/model type(s) are used?]]  [[Regression]], [[K-Nearest Neighbors (KNN)]], [[Neural Network#Deep Neural Network (DNN)|Deep Neural Network (DNN)]], [[Natural Language Processing (NLP)]], [[Association Rule Learning]], etc.
@@ Line 150: / Line 150: @@
 * [[PRIMO.ai#Development & Implementation|What is the development & implementation plan]]?
 ** What foundational capabilities are defined or in place for the AI investment? infrastructure platform, cloud resources?
-*** What languages & scripting are/will be used? e.g. [[Python]], [[Javascript]], [[PyTorch]]
+*** What languages & scripting are/will be used? e.g. [[Python]], [[JavaScript]], [[PyTorch]]
 *** What [[Libraries & Frameworks]] are used?
 *** Are [[Notebooks|notebooks]] used?  If so, is [[Jupyter]] supported?

@@ Line 137: / Line 137: @@
 * What tool(s) are used or will be used for model management?
 ** How are [[Algorithm Administration#Hyperparameter|Hyperparameters]] managed? What optimizers are used, e.g. [[Algorithm Administration#Automated Learning|automated learning (AutoML)]]?
-** What components, e.g. optimizer, tuner, training, [[Algorithm Administration#Versioning|versioning]], model dependencies; e.g. training data, [[Datasets|dataset(s)]], historical lineage, [[Writing / Publishing#Model Publishing|publishing]], performance evaluations, and model storing are integrated in the model management tool(s)?
+** What components, e.g. optimizer, tuner, training, [[Algorithm Administration#Versioning|versioning]], model dependencies; e.g. training data, [[Datasets|dataset(s)]], historical lineage, [[Writing/Publishing#Model Publishing|publishing]], performance evaluations, and model storing are integrated in the model management tool(s)?
 ** What is the reuse strategy? Is there a single POC for the reuse process/tools?
 *** Are the AI models published (repo, marketplace) for reuse, if so where?

@@ Line 199: / Line 199: @@
 ** [[Evaluation - Measures#Specificity|Specificity]]
 ** [[Project Management#Return on Investment (ROI)|Return on Investment (ROI)]]
 * [[AI Governance]] / [[Algorithm Administration]]
 * [[AI Verification and Validation]]

@@ Line 19: / Line 19: @@
 [https://news.google.com/search?q=ai+Technical+Assessment+Evaluation+project+review+performance ...Google News]
 [https://www.bing.com/news/search?q=ai+Technical+Assessment+Evaluation+project+review+performance&qft=interval%3d%228%22 ...Bing News]
 <hr>
 <center><b>Prompts for assessing AI projects</b></center>

@@ Line 19: / Line 19: @@
 [https://news.google.com/search?q=ai+Technical+Assessment+Evaluation+project+review+performance ...Google News]
 [https://www.bing.com/news/search?q=ai+Technical+Assessment+Evaluation+project+review+performance&qft=interval%3d%228%22 ...Bing News]
 * [[Strategy & Tactics]] ... [[Project Management]] ... [[Best Practices]] ... [[Checklists]] ... [[Project Check-in]] ... [[Evaluation]] ... [[Evaluation - Measures|Measures]]

← Older revision		Revision as of 16:31, 30 June 2023
Line 20:		Line 20:
	[https://www.bing.com/news/search?q=ai+Technical+Assessment+Evaluation+project+review+performance&qft=interval%3d%228%22 ...Bing News]		[https://www.bing.com/news/search?q=ai+Technical+Assessment+Evaluation+project+review+performance&qft=interval%3d%228%22 ...Bing News]

		+	* [[Strategy & Tactics]] ... [[Project Management]] ... [[Best Practices]] ... [[Checklists]] ... [[Project Check-in]] ... [[Evaluation]] ... [[Evaluation - Measures\|Measures]]
	<center><b>Prompts for assessing AI projects</b></center>		<center><b>Prompts for assessing AI projects</b></center>

@@ Line 2: / Line 2: @@
 |title=PRIMO.ai
 |titlemode=append
-|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
+|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
 [https://www.youtube.com/results?search_query=ai+Technical+Assessment+Evaluation+project+review+performance YouTube]

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 *** Will any [[Data Quality#Data Augmentation, Data Labeling, and Auto-Tagging|data labeling be required?  Is the data augmented? Is auto-tagging used?]] What data augmentation tools are/will be used?
 *** Have the key features/data attributes to be used in the AI model been identified?
-*** Will the labeling be enabled by merging domain knowledge with [[Natural Language Processing (NLP)#Ontology|ontologies]]?  If so, have concepts and associations been identified?
+*** Will the labeling be enabled by merging domain knowledge with [[Graph#Ontology|ontologies]]?  If so, have concepts and associations been identified?
 *** How good is the quality of the data labeling? How close is the [[Data Science#Ground Truth|ground truth]] to being a gold standard?
 *** What [[Feature Exploration/Learning|data/feature exploration/engineering processes and tools are in place or being considered?]]

@@ Line 146: / Line 146: @@
 *** What tools are used for the [[Algorithm Administration#AIOps/MLOps|AIOps]]?  Please identify those on-premises and online services?
 *** Are the AI languages, libraries, scripting, and [[Algorithm Administration#AIOps/MLOps|AIOps]] applications registered in the organization?
-** Are the processes and decisions [[Enterprise Architecture (EA)|architecture]] driven to allow for end-to-end visibility and allow for dependency management?  Is information mapped to the intended use to allow [[Analytics|analytics]] and [[Visualization|visualizations]] framed in [[Framing Context|context]]?
+** Are the processes and decisions [[Enterprise Architecture (EA)|architecture]] driven to allow for end-to-end visibility and allow for dependency management?  Is information mapped to the intended use to allow [[Analytics|analytics]] and [[Visualization|visualizations]] framed in [[context]]?
 *** Does the AI investment depict the [[Algorithm Administration#AIOps/MLOps|AIOps]] pipeline/toolchain applications in its architecture, e.g tech stack?
 *** Does the [[Algorithm Administration#AIOps/MLOps|SecDevOps]] depict the AI investment in its architecture and how the health metrics are depicted?