Murphy p z (18 Ergebnisse)
Verlag: Lionsgate Miramax 2011-08-23 00:00:00, 2011
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Radical History Review - Queering Archives, Intimate Tracings
MARSHAL, DANIEL (ed.), MURPHY, KEVIN P. (ed.), TORTORICI, ZEB (ed.)
Verlag: MARHO: The Radical Historians Organisaiton 2015, 2015
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Radical History Review: Issue 120
MARSHALL, DANIEL (ed.) & MURPHY, KEVIN P. (ed.) & TORTORICI, ZEB (ed.)
Verlag: Duke University Press 2014, 2014
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paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2016-06-01 Pages: 432 Publisher: Xi'an Jiaotong University Press AP US History 5 points to win is divided into five steps to help students understand their own level and AP exams. training skills exam. review the key and difficult. sit establish confidence. The book describes in detail the characteristics of the AP exam. and provides three different pro forma programs to help candidates develop a review plan according to their own situation. Diagnostic te.…

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Paperback. Zustand: new. Paperback. The one book that explains every major LLM - what each does best, what each costs, and how to deploy them in your business. The AI landscape is bewildering. A dozen models compete for attention, the marketing claims are contradictory, and the practical question - "which model should I use for what?" - remains surprisingly hard to answer. The LLM Manual is that answer. Strategy consultant P.Z. Murphy delivers a practical, comparative, opinionated guide covering Claude, GPT-4, Gemini, Llama, Mistral, and the broader ecosystem. Each model is assessed with candid analysis of strengths, weaknesses, and ideal use cases. Side-by-side comparison tables cut through the noise. Original frameworks you'll use immediately: - SCORE - the 5-factor model selection framework (Sophistication, Context, Output, Responsiveness, Economics)- CRAFT - the prompting framework that turns vague instructions into professional-quality output- Cost Optimization Hierarchy - 5 levers to reduce LLM costs by 60-80%- AI Data Classification - 4-tier security framework for enterprise governance- AI Maturity Model - map your organization's journey from experimentation to transformation Complete business application coverage: Sales, marketing, customer success, finance, legal, operations, product, engineering, and data - with specific use cases, prompting strategies, and implementation guidance for each function. Plus: API and platform comparison, RAG architecture explained, ROI modeling, regulatory compliance, change management, and quick-reference model cards in the appendix. Whether you're a CEO setting AI strategy, a functional leader choosing tools, or an implementer building applications - this manual gives you everything you need in one place. Start small. Start now. Build from there. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

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Paperback. Zustand: new. Paperback. The one book that explains every major LLM - what each does best, what each costs, and how to deploy them in your business. The AI landscape is bewildering. A dozen models compete for attention, the marketing claims are contradictory, and the practical question - "which model should I use for what?" - remains surprisingly hard to answer. The LLM Manual is that answer. Strategy consultant P.Z. Murphy delivers a practical, comparative, opinionated guide covering Claude, GPT-4, Gemini, Llama, Mistral, and the broader ecosystem. Each model is assessed with candid analysis of strengths, weaknesses, and ideal use cases. Side-by-side comparison tables cut through the noise. Original frameworks you'll use immediately: - SCORE - the 5-factor model selection framework (Sophistication, Context, Output, Responsiveness, Economics)- CRAFT - the prompting framework that turns vague instructions into professional-quality output- Cost Optimization Hierarchy - 5 levers to reduce LLM costs by 60-80%- AI Data Classification - 4-tier security framework for enterprise governance- AI Maturity Model - map your organization's journey from experimentation to transformation Complete business application coverage: Sales, marketing, customer success, finance, legal, operations, product, engineering, and data - with specific use cases, prompting strategies, and implementation guidance for each function. Plus: API and platform comparison, RAG architecture explained, ROI modeling, regulatory compliance, change management, and quick-reference model cards in the appendix. Whether you're a CEO setting AI strategy, a functional leader choosing tools, or an implementer building applications - this manual gives you everything you need in one place. Start small. Start now. Build from there. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

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Paperback. Zustand: new. Paperback. Your AI/ML clients are leaving R&D credits on the table - and the ones who are claiming them aren't documenting at the level the IRS now expects.The One Big Beautiful Bill Act rewrote 174 expensing rules in July 2025. Section 41 four-part test enforcement has tightened in parallel. And every CPA with R&D credit clients is relearning the game in real time, while AI/ML companies - the fastest-growing segment of qualified claimants - flood the market with software development costs that may or may not qualify.This Playbook is for the practitioner who needs to get this right. Not a general overview. A working manual for qualifying, computing, and defending 41 claims for AI/ML clients in the post-OBBBA environment, with AI used as both subject (what counts as qualified research for AI development) and tool (how to surface QREs and draft audit-defensible technical narratives at scale).What's inside: Four-part test checklists for AI/ML projects - model architecture, training pipelines, fine-tuning (qualifying); prompt tweaking, off-the-shelf deployment (not qualifying)27 sample QRE narratives covering common AI development patterns, ready to adaptPost-OBBBA 174 / 41 computation walkthroughs with worked examplesAI-assisted documentation workflows that hold up under IRS examAudit defense templates: substantiation memos, time-tracking frameworks, contemporaneous documentation protocolsEngagement letter language and scoping templates for R&D credit workRed flags: positions that look qualifying but won't survive examinationWritten for: CPAs running R&D credit engagements, R&D specialty firm consultants, in-house tax directors at AI/ML companies, tax attorneys advising on 41 positions, and tax controversy attorneys defending 41 credits under examination. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Zustand: new. Paperback. Your AI/ML clients are leaving R&D credits on the table - and the ones who are claiming them aren't documenting at the level the IRS now expects.The One Big Beautiful Bill Act rewrote 174 expensing rules in July 2025. Section 41 four-part test enforcement has tightened in parallel. And every CPA with R&D credit clients is relearning the game in real time, while AI/ML companies - the fastest-growing segment of qualified claimants - flood the market with software development costs that may or may not qualify.This Playbook is for the practitioner who needs to get this right. Not a general overview. A working manual for qualifying, computing, and defending 41 claims for AI/ML clients in the post-OBBBA environment, with AI used as both subject (what counts as qualified research for AI development) and tool (how to surface QREs and draft audit-defensible technical narratives at scale).What's inside: Four-part test checklists for AI/ML projects - model architecture, training pipelines, fine-tuning (qualifying); prompt tweaking, off-the-shelf deployment (not qualifying)27 sample QRE narratives covering common AI development patterns, ready to adaptPost-OBBBA 174 / 41 computation walkthroughs with worked examplesAI-assisted documentation workflows that hold up under IRS examAudit defense templates: substantiation memos, time-tracking frameworks, contemporaneous documentation protocolsEngagement letter language and scoping templates for R&D credit workRed flags: positions that look qualifying but won't survive examinationWritten for: CPAs running R&D credit engagements, R&D specialty firm consultants, in-house tax directors at AI/ML companies, tax attorneys advising on 41 positions, and tax controversy attorneys defending 41 credits under examination. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…