Posts Tagged ‘Agents’
[DotJs2025] Prompting is the New Scripting: Meet GenAIScript
As generative paradigms proliferate, scripting’s syntax strains under AI’s amorphous allure—prompts as prosaic prose, yet perilous in precision. Yohan Lasorsa, Microsoft’s principal developer advocate and Angular GDE, unveiled GenAIScript at dotJS 2025, a JS-inflected idiom abstracting LLM labyrinths into lucid loops. With 15 years traversing IoT’s interstices to cloud’s canopies, Yohan likened this lexicon to jQuery’s jubilee: DOM’s discord domesticated, now GenAI’s gyrations gentled for mortal makers.
Yohan’s yarn recalled jQuery’s jihad: browser balkanization banished, events etherealized—20 years on, GenAI’s gale mirrors, models multiplying, APIs anarchic. GenAIScript’s grace: JS carapace cloaking complexities—await ai.chat('prompt') birthing banter, ai.forEach(items, 'summarize') distilling dossiers. Demos danced: file foragers (fs.readFile), prompt pipelines (ai.pipe(model).chat(query)), even AST adventurers refactoring Angular artifacts—CLI’s churn supplanted by semantic sorcery.
This superstructure spans: agents’ autonomy (ai.agent({tools})), RAG’s retrieval (ai.retrieve({query, store})), even vision’s vignettes (ai.vision(image)). Yohan’s yield: ergonomics eclipsing exhaustion—built-ins for Bedrock, Ollama; extensibility via plugins. Caveat’s cadence: tool for tinkering, not titanic tomes—yet frameworks’ fledglings may flock hither.
GenAIScript’s gospel: prompting’s poetry, scripted sans strife—democratizing discernment in AI’s ascent.
jQuery’s Echo in AI’s Era
Yohan juxtaposed jQuery’s quirk-quelling with GenAI’s gale—models’ menagerie, APIs’ anarchy. GenAIScript’s girdle: JS’s jacket jacketting journeys—chat’s cadence, forEach’s finesse.
Patterns’ Parade and Potentials
Agents’ agency, RAG’s recall—pipelines pure, vision’s vista. Yohan’s yarns: Angular migrations mended, Bedrock bridged—plugins’ pliancy promising proliferation.
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[DotAI2024] DotAI 2024: Pierre Stock – Unleashing Edge Agents with Compact Powerhouses
Pierre Stock, VP of Science Operations at Mistral AI and a vanguard in efficient deployment, dissected edge AI’s promise at DotAI 2024. From Meta’s privacy-preserving federated learning to Mistral’s inaugural hire, Stock champions compact models—1-3B parameters—that rival behemoths in latency-bound realms like mobiles and wearables, prioritizing confidentiality and responsiveness.
Sculpting Efficiency in Constrained Realms
Stock introduced Ministral family: 3B and 8B variants, thrice slimmer than Llama-3’s 8B kin, yet surpassing on coding benchmarks via native function calling. Pixtral 12B, a vision-text hybrid, outpaces Llama-3-Vision 90B in captioning, underscoring scale’s diminishing returns for edge viability.
Customization reigns: fine-tuning on domain corpora—legal tomes or medical scans—tailors inference without ballooning footprints. Stock advocated speculative decoding and quantization—4-bit weights halving memory—to squeeze sub-second latencies on smartphones.
Agents thrive here: function calling, where models invoke tools via JSON schemas, conserves tokens—each call equaling thousands—enabling tool orchestration sans exhaustive contexts.
Orchestrating Autonomous Edge Ecosystems
Stock demoed Le Chat’s agentic scaffolding: high-level directives trigger context retrieval and tool chains, like calendaring via API handoffs. Native chaining—parallel tool summons—amplifies autonomy, from SQL queries to transaction validations.
Mistral’s platform simplifies: select models, infuse instructions, connect externalities—yielding JSON-formatted outputs for seamless integration. This modularity, Stock asserted, demystifies agency: no arcane rituals, just declarative intents yielding executable flows.
Future vistas: on-device personalization, where federated updates hone models sans data exodus. Stock urged experimentation—build agents atop Ministral, probe boundaries—heralding an era where intelligence permeates pockets, unhindered by clouds.