How to Safely Get Started with Large Language Models
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Just as a skydiver never wishes they’d left their parachute behind, no business...
for the health of people
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FOR THE HEALTH OF PEOPLE: EQUITY
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“The work [with Synaptiq] is unprecedented in its scale and potential impact,” Mortenson Center’s Managing Director Laura MacDonald MacDonald said. “It ties together our center’s strengths in impact evaluation and sensor deployment to generate evidence that informs development tools, policy, and practice.”
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DATA STRATEGY
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A startup in digital health trained a risk model to open up a robust, precise, and scalable processing pipeline so providers could move faster, and patients could move with confidence after spinal surgery.
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PREDICTIVE ANALYTICS
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Thwart errors, relieve in-take form exhaustion, and build a more accurate data picture for patients in chronic pain? Those who prefer the natural albeit comprehensive path to health and wellness said: sign me up.
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MACHINE VISION
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Using a dynamic machine vision solution for detecting plaques in the carotid artery and providing care teams with rapid answers, saves lives with early disease detection and monitoring.
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INTELLIGENT AUTOMATION
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This global law firm needed to be fast, adaptive, and provide unrivaled client service under pressure, intelligent automation did just that plus it made time for what matters most: meaningful human interactions.
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Mushrooms, Goats, and Machine Learning: What do they all have in common? You may never know unless you get started exploring the fundamentals of Machine Learning with Dr. Tim Oates, Synaptiq's Chief Data Scientist. You can read and visualize his new book in Python, tinker with inputs, and practice machine learning techniques for free. |
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By: Synaptiq 1 Jul 22, 2022 8:00:00 AM
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In the United States, the rise of artificial intelligence (AI) drives a race between regulators and the companies under their jurisdiction. Stanford University reports that private investment in AI more than doubled from 2020 to 2021, while the government scrambled to keep pace. Although the legislative record shows a 30 percent increase in the number of federal-level bills with AI provisions from 2020 to 2021, only 2 percent were passed into law.
What does this mean? The use of AI by companies in the U.S. remains largely unregulated at the federal level, but this may soon change. Although the federal legislature is divided on AI, state lawmakers have rallied in support of regulation. About 20 percent of the state-level AI-related bills proposed in 2021 became law. Furthermore, support for AI regulation crosses regional and partisan lines. Forty-one of 50 states proposed at least one AI-related bill in 2021, totaling 131 state-level bills sponsored by 79 Democrats and 40 Republicans.
A 2021 report by the Congressional Research Service notes that Congress has been “increasingly engaged [...] working to address policy concerns arising from AI development and use.” Top concerns include the impact of AI-driven automation on the workforce, standards for AI systems, and AI-related ethics considerations.
Historically, the U.S. government has taken a nuanced, multi-faceted approach to AI regulation—investing heavily in the technology while also voicing concerns about its potential to create regulatory challenges. For example, Jason Furman, the Chair of President Obama’s Council of Economic Advisers, wrote: "The biggest worry I have about AI is that we will not have enough of it," while President Obama himself cautioned, "as technologies [like AI] emerge and mature, figuring out how they get incorporated into existing regulatory structures becomes a tougher problem, and the government needs to be involved a little bit more."
Ultimately, it’s unclear what path the U.S. government will choose. Will caution inspire a regulatory crackdown? Or, will economic interests spark greater investment? The answer could be both or neither.
One thing is certain: private companies should be prepared for anything. We recommend staying “ahead of the curve” by engaging in proactive activities such as tracking legislative developments, communicating with government representatives, and considering the impact of AI from a multifaceted, diverse perspective.
Synaptiq is an Oregon-based AI and data science consulting firm. We engage our clients in a collaborative approach to developing custom, human-centered solutions with a commitment to ethics and innovation.
Contact us if you have a problem to solve, a process to refine, or a question to ask.
You can learn more about our story through our past projects, blog, or podcast.
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