Big Tech Moves Toward Specialized AI and Immersive Retail | PYMNTS.com
From task-tuned AI to brick-and-mortar immersion, tech giants are shifting away from one-size-fits-all platforms. Meta is carving its stack into specialized models, Netflix is translating streaming IP into walkable worlds, Microsoft is learning how people actually use AI day-to-day, and Salesforce is putting autonomous agents directly into sales funnels. The connective tissue: precision, orchestration and new ways to engage consumers both online and in person.
Meta Splinters Its AI Into Specialists
Meta is building two complementary models as it doubles down on purpose-built AI. Internally code-named Mango and Avocado, the systems target different modalities: Mango is aimed at image and video generation and editing, while Avocado focuses on text reasoning and coding.
By swapping a monolithic approach for a portfolio of specialists, Meta is optimizing for quality, latency and cost across creative and conversational use cases. Mango is tailored to short-form video, ad creative and creator tools that power social feeds. Avocado underpins chat, search and developer workflows. The plan is to weave these models across Facebook, Instagram and other surfaces so each task is handled by the best-fit engine rather than forcing a single generalist to do it all.
The endgame: smarter creative production, tighter control of infrastructure spend and better alignment with the way people actually create and consume visual and textual content.
Netflix Turns Fandom Into a Place You Can Walk Through
Streaming is stepping into the physical world with Netflix House, a permanent venue designed to immerse visitors inside hit franchises. Instead of limited pop-ups, this is a year-round destination—part theme environment, part interactive game space, part retail and dining hub.
Guests move through adaptive installations themed to blockbuster series, participate in challenges and explore environments that respond to their choices. It’s location-based entertainment built with personalization in mind: what people touch, where they linger and how they play can inform future experiences and even storytelling. Beyond deepening fandom, the concept opens fresh revenue streams through ticketing, merchandise and food, while converting passive viewership into active participation.
Copilot Usage Shows Health Questions Lead on Mobile
New usage patterns around Microsoft’s Copilot highlight a split between contexts. On phones, health and wellness topics dominate—everything from symptoms to mental health prompts—signaling a growing tendency to consult AI for everyday decisions. On desktops, professional and technical queries are more common, reflecting work-mode use.
That divergence raises familiar questions about accuracy, safeguards and responsible design, especially for sensitive topics. It also underscores the need for context-aware guardrails: an assistant should adapt tone, disclaimers and suggested next steps depending on the scenario. Insights like these are feeding how safety controls and responses are tuned across personal and professional use cases.
Salesforce Bets on Agentic AI With Qualified Acquisition
Salesforce is acquiring Qualified to embed autonomous agents directly into sales and marketing workflows. Rather than waiting for a human rep, Qualified’s software can identify high-intent buyers, start conversations, qualify leads, route them in real time and trigger actions across the CRM.
It’s a pragmatic shift from assistive AI to agentic AI, granting software bounded authority to take the first step. Folded into Salesforce’s Agentforce strategy, the approach targets faster response times, higher conversion and tighter orchestration across marketing, sales and service. Expect more proactive outreach, richer context at handoff and less friction inside revenue operations.
The Big Picture: Specialization + Immersion
Across these moves, a clear pattern emerges. AI stacks are being decomposed into specialist models—visual, textual, agentic—so each job gets an engine tuned to its needs. At the same time, entertainment and retail are blending into physical-digital experiences that produce richer engagement signals.
- For creators and advertisers: more powerful tools for video and image generation, plus faster iteration on campaign assets.
- For location-based retail and entertainment: immersive venues as continuous data sources and monetization channels.
- For AI platforms: context-sensitive safety frameworks, especially for health-related queries.
- For B2B teams: autonomous agents that move from assist to action, with guardrails, logs and policy controls.
The throughline is orchestration—deciding which model or agent runs when, how experiences adapt on the fly and what feedback loops improve the next interaction. As these bets scale, expect feeds that feel more bespoke, assistants that are more situationally aware and venues that turn fandom into something you can literally step into.
