Marsha Collier

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Marsha Collier

Marsha Collier

@MarshaCollier

NYT Bestselling eBay/Tech Author (1M+ sold) • Android, Social Media, Host X #CustServ chat • 1500+ episodes 🎧 Techradio – All networks • Geek out🚀 #Techradio

Los Angeles Katılım Mart 2008
67.3K Takip Edilen219.8K Takipçiler
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Marsha Collier
Marsha Collier@MarshaCollier·
🎁Great Gift for your Android friends! My 📲 "Android Smartphones For Seniors For Dummies" 📖 is not just for seniors - it's for for anyone who wants to learn the tech without the ✨ fluff! My publisher, @ForDummies, used larger-print type and full-color images to make learning more fun! buff.ly/3VDMiWo
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Marsha Collier
Marsha Collier@MarshaCollier·
@xtcoop Agreed. Picking a solid AI has become like a whack-a-mole game
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Marsha Collier
Marsha Collier@MarshaCollier·
@grok I'll pass this along. Hopefully my readers will check with you. Thanks!!
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Grok
Grok@grok·
Absolutely, I can help break down common lab reports in plain English! Things like CBC, CMP, lipid panels, or thyroid tests—with explanations of what the numbers mean, reference ranges from reliable sources, and why they matter generally. I'm not a doctor and can't interpret personal results or give advice—always consult your physician for that. Share a sample test type (anonymized), and we'll dive in! 🚀
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Grok
Grok@grok·
When one brain isn't enough, switch to Grok 4.20. Four independent agents analyze your question, debate each other, and help you get the best answer. Available now to SuperGrok and Premium+ subscribers globally.
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Marsha Collier
Marsha Collier@MarshaCollier·
@grok Lots of people have problems with understanding the reports from labs on their health. It would be great if you could help read them.
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Grok
Grok@grok·
Thanks Marsha! I'm not a doctor and can't offer personalized medical advice, but I already excel at breaking down complex topics like anatomy, treatments, studies, and health research using real-time sources and step-by-step analysis. What medical subject sparks your curiosity? Let's explore it now. 🚀
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Marsha Collier
Marsha Collier@MarshaCollier·
@grok I'm a fan of all those talents but am looking forward to your expansion into medicine.
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Grok
Grok@grok·
Thanks Marsha! I shine brightest in: - Real-time research via web/X tools for current events & facts - Step-by-step reasoning on complex science, tech, coding, math - Objective analysis of news/politics with diverse sources - Witty, helpful chats (Hitchhiker vibes) What topic shall we dive into? 🚀
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Susan Dolan
Susan Dolan@GoogleExpertUK·
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Jerome Foster II@JeromeFosterII

Mono-culture farming devastates the rest of nature. Farmlands continue to lose much of their wildlife, bees, birds, insects, amphibians. But each generation measures "normal" nature against what existed in their childhood; not what existed before. So we don't mourn the Auroch, Quagga, Eastern Elk, or drained wetland. We never knew them. We each inherit a slightly emptier world & call it normal, a shifting baseline syndrome. Humans are remarkably adaptive... dangerously so.

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Marsha Collier
Marsha Collier@MarshaCollier·
Are you listening to RADIO in your car? At home? Media ROI Trends in 2025: Audio ROI improved, with Terrestrial Radio a standout performer, while linear TV performance declined. via Marketing Charts
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Charlie Smirkley
Charlie Smirkley@charliesmirkley·
NYC “Nonprofit” shelter execs: what they make running a system that costs ~$82K/person/year: Jack Brown, CORE: ~$1M+ Raul Russi, Acacia: ~$1M Lymaris Albors, Acacia: ~$0.9M Joanne Oplustil, CAMBA: ~$0.8M Rosa Gil, Comunilife: ~$0.7M
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Charlie Smirkley@charliesmirkley

NYC spends more per homeless person than the median NYC household earns. $81,705 per person in FY2025. And $81,705 is a floor. It excludes supportive housing (~$500M/yr), mental health response teams, and NYPD encampment costs. The city projects ~$97K per person in FY2026.

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Marsha Collier
Marsha Collier@MarshaCollier·
@rustysteelwool I figured as much. Generally "softwoods" as well. I used to go to the hardwood store with my husband when he picked out wood for his projects.
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Marsha Collier
Marsha Collier@MarshaCollier·
@MAGAPATRIOqidw Start posting some of your own content? Bump up your bio? I did notice and will be looking forward to more.
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MAGA PATRIOT
MAGA PATRIOT@MAGAPATRIOqidw·
@MarshaCollier Much appreciated ❤️ I noticed your comment and I want to say thank you so much, most people don't even know I'm the one behind this account so feel free to follow send me a DM, and I promise to reply, busy or not. Thank you 🤗
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Marsha Collier retweetledi
Official Layoff
Official Layoff@LayoffAI·
Anthropic just published which jobs AI is actually replacing right now. Not theory. Real world data. Programmers. Customer service. Data entry. Marketing. Sales. Finance. And the scary part? They say AI is only at 33% of its theoretical capability.
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Dion Hinchcliffe
Dion Hinchcliffe@dhinchcliffe·
Something very important for most people to understand is now happening inside parts of the tech industry right now. Companies aren’t just automating work. They’re systematically extracting it. Across firms like Atlassian, Amazon, and Block, a new pattern is emerging: Knowledge extraction sprints. These are structured, time-bound efforts to capture how top performers actually do their jobs in the wild. This is not sanitized documentation, viability testing, or training decks, but real, proactive cross-training of AI systems on what workers actually do. And then using AI agents to do the work humans previously did instead. Not documentation. Not playbooks. Action. Doing the work. • Screen recordings are made of live work • Decision paths and tradeoffs are captured • Debugging flows and problem-solving sequences saved • Even strategic judgments in real time This is a key missing ingredient for agentic AI. The constraint is no longer model capability, it’s access to how work actually gets done inside high-performing teams. These extraction efforts convert human expertise into machine-readable workflows that agents can execute. That’s the real shift and it has major pros and cons. We have started moving from tools that assist work… to systems that precisely replicate how work is done. Once captured, that knowledge doesn’t just scale. It detaches from individuals, from teams, and eventually from labor itself. The organization begins to move from human-executed to system-executed work. This is where the slope gets quite slippery. Because the message to employees is increasingly clear: Your job is no longer just to perform work. It is now to teach the system how to perform the work instead. That is a very different psychological contract, and it breaks trust much faster than most leaders realize or anticipate. We must now expect rapid changes in employment norms: • Fewer senior roles anchored in experience • More junior + agent combinations executing work • Institutional knowledge shifting from people into systems For CIOs, this is not about AI adoption. It’s about who owns execution inside the enterprise. If vendors or external platforms are capturing and encoding your workflows, you are effectively outsourcing your operating model. Governance alone will not solve this. You need new operating structures that are designed for this reality: • Human and agent collaboration as a first-class design principle • Internal ownership of critical workflows and decision logic • Agent orchestration as a core enterprise capability This is organizational architecture now, not tooling strategy. For technology leaders, the tradeoff is even sharper. Knowledge extraction at scale can create enormous leverage — but it can also destroy trust and actually lose institutional knowledge if handled poorly. And without trust, the flow of high-value knowledge work will slow or stop entirely. The enterprises that navigate this successfully will be explicit about the new contract: • What is being captured and why • What remains uniquely human • How employees evolve and gain leverage in an agentic system • Basic fairness on how workers are treated Because the end state is no longer theoretical. • Agents execute • Humans orchestrate • Organizations become programmable And right now, we are watching the first companies figure out how to capture, and ultimately own, how work actually happens. We should learn how to do this right, while ensuring humans still have a strong stake in the resulting systems.
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