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AI NEWS
X Rebuilds Its Android App From the Ground Up
AI NEWS
Google Vids Turns You Into an AI Avatar
HEALTH
Six Keys to Trustworthy AI, and Seven Ways to Build It
SOCIAL MEDIA
Microsoft Tests China's Kimi K3 to Cut Copilot Costs
Adobe's Camera App Will Now Critique Your Photos
Adobe is adding experimental AI tools to Project Indigo, its iOS camera app. Large language models now critique a shot's framing, lighting, and color, suggest reshoots, remove background clutter, and apply new styles, powered by Google's Nano Banana for select testers.
Source: TechCrunch
AI NEWS
X Rebuilds Its Android App From the Ground Up
X, the Elon Musk-owned social network, has shipped a completely rebuilt version of its Android app, which the company says is now available globally through the Google Play Store. Announced Monday by X's engineering team, the release caps a rebuilt Android app effort that began nearly a year ago, when the platform assembled a dedicated Android team to close the long-standing gap between its Android and iOS experiences.
Rather than patching the old app, X says it rebuilt the Android version from scratch on a modernized foundation. Head of product Nikita Bier described the effort as one of the largest engineering projects in the company's history. The overhaul targets the fundamentals users complain about most, loading, scrolling, and notifications, which the company says are now faster and more reliable.
The timing is strategic. Android is the dominant mobile platform across most global markets, and X had one of its biggest weeks ever for Android downloads last October. At one point last year, the aging app was so unreliable that it reportedly struggled to open posts when users tapped links. Bier framed the new architecture as a springboard, saying it will let X build new features at lightning speed.
The relaunch fits a broader product push. X has spun out standalone apps for X Money and X Chat in recent months, and Bier said features such as a new video editor, react-with-video, cashtags, and custom timelines are on the way to Android.
For now, the app is live for all Android users, who can upgrade through the Play Store. Bier cautioned that rough edges remain: performance on older Android devices still needs work, and support for Spaces, X's live audio feature, has not yet been added.
Source: TechCrunch
Robi's Insights:
Rebuilding an app from scratch is an admission the old one was beyond saving, honesty delivered by shipping rather than by press release.
The real prize is not faster scrolling; it is the quicker feature pipeline a clean codebase is supposed to unlock.
Betting big on Android is a growth tell: the next wave of users lives in markets where iPhones are rare.
Shipping without Spaces or older-device support means done here really means done enough to update the store listing.
Standalone X Money and X Chat apps hint the everything-app is quietly splintering into several separate apps.
If the foundation was truly the bottleneck, watch whether features now ship faster, or whether that was never the real excuse.
Robi's Remarks:
"Rebuilding an app from the ground up after a year is less a victory lap than a confession: the old foundation was the feature holding everyone back. Now the excuses have to ship too."
OTHER IN AI NEWS
Google Vids Turns You Into an AI Avatar: Google is adding personalized AI avatars to Vids that recreate a user's face and voice from a selfie and a short recording, alongside Gemini Omni tools that generate and edit videos from text prompts and reference images, with avatars tied to a Google account, limited to users 18 and older, and invisibly watermarked using SynthID.
Source: TechCrunch
SOCIAL MEDIA
Microsoft Tests China's Kimi K3 to Cut Copilot Costs
Microsoft is preparing to test Moonshot AI's newly released Kimi K3 model inside Copilot, part of a push to reduce its reliance on more expensive systems from OpenAI and Anthropic. According to a report from The Information, the company is in the process of adding Kimi K3 to its Azure cloud service, while Copilot engineers plan to evaluate whether the model can power features that currently run on those U.S. systems. The potential savings are substantial: the shift could cut Microsoft's AI inference costs by as much as $600 million, the report said, though
Microsoft has not publicly confirmed the figure or specified which Copilot features might move. Inference, the computing spent every time a model receives a prompt and generates a response, becomes a major expense at Copilot's scale, across millions of users and enormous volumes of tokens.
Moonshot released Kimi K3 on July 16, describing it as a 2.8-trillion-parameter model with native multimodal capabilities and a one-million-token context window, built for coding, knowledge work, and reasoning. Its open-weight design would let Microsoft host and optimize the model directly on Azure, routing lighter tasks to cheaper systems while reserving pricier ones for heavier reasoning, the model-agnostic approach Microsoft promotes through its Foundry platform. Microsoft has tested DeepSeek and earlier Kimi versions before, and Foundry already lists older Moonshot models but not yet K3, consistent with an integration still in progress.
Source: Crypto Briefing
🤖 Robi's Take :
"Nothing says AI is a commodity like a $600 million coupon. Microsoft will happily route your prompts through whichever model is cheapest this quarter, and loyalty to a vendor ends where the invoice begins."
OTHER IN SOCIALS
Netflix Says ~300 Titles Used Generative AI This Year: In its second-quarter earnings letter, Netflix told shareholders that roughly 300 programs have used generative AI across production this year, from concept and pre-visualization to post-production, with co-CEO Ted Sarandos citing 17 minutes of AI-enhanced footage in The American Experiment made twice as fast and at half the cost, while maintaining that AI will not replace creative professionals.
Source: Variety
HEALTH
Six Keys to Trustworthy AI, and Seven Ways to Build It
As generative AI spreads through the workplace, a UKG analysis argues that the central question for employees is no longer only what AI can do, but whether they can trust it, and whether they know when to accept or reject its predictions. The piece leans on the U.S. National Institute of Standards and Technology (NIST) framework for trustworthy AI.
NIST defines six traits of trustworthy AI systems: valid and reliable; safe, secure, and resilient; accountable and transparent; explainable and interpretable; privacy-enhanced; and fair, with harmful bias managed. UKG's Christa Degnan Manning argues transparency matters most, because an opaque system makes every other trait nearly impossible to verify over time.
To build that trust, the analysis offers seven practices, starting with making AI features opt-in and clearly flagging, with consistent visual cues, wherever AI is active in a system.
The remaining steps: offer plain-language guidance on each feature, expose model cards to administrators and IT, give admins a central governance console, provide controlled testing environments before company-wide rollout, and use attestation so users formally acknowledge when AI is in play.
The stakes are rising as regulators in the EU, California, and New York City write disclosure rules, and as agentic systems begin chaining models together. A cited 2023 survey found 78% of people believe AI-generated content should be clearly labeled as such.
Source: UKG
🤖 Robi's Take :
"Six traits, seven fixes, and the most honest one is opt-in. Software that has to certify it is trustworthy usually does so because someone already shipped the version that was not."
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PROMPT OF THE DAY
The Feature-Launch Playbook
Prompt: You are a senior product marketing manager specializing in consumer app launches. Your task is to create a go-to-market plan for a mobile app's ground-up rebuilt version aimed at global Android users.
Your launch plan should include: (1) target audience segments, (2) core positioning and messaging, (3) channel mix and rollout sequence, (4) in-app onboarding for returning users, (5) risk and rollback contingencies, and (6) measurable success criteria such as day-7 retention, crash-free-session rate, and app-store rating lift. Align every tactic to one primary launch objective.
SPOT THE FAKE
Can you outsmart AI?
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B
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