The Cool Stuff Only Happens at Scale
a16z Podcast5 Juni 2015

The Cool Stuff Only Happens at Scale

Distributed computing frameworks like Hadoop and Spark have enabled processing of "big data" sets -- but that's not enough for modeling surprise/rare "black swan" or complex events. Just think of scenarios in disaster planning (earthquakes, terrorist attacks, financial system collapse); biology (including disease); urban planning (cities, transportation, energy power grids); military defense ... and other complex systems where unknown behaviors and properties can emerge.

They can't be modeled based on (by definition impossible) limited data. And parallelization for this is hard. But what if companies and governments could answer these seemingly impossible questions -- through simulations? Especially ones where we can directly merge in knowledge and cues from the real world (sensors, sensors everywhere)? CEO of Improbable Herman Narula and Stanford University professor-in-residence at a16z Vijay Pande discuss this and more with Chris Dixon in this episode of the a16z Podcast. And as Herman says, "the cool stuff only happens at scale".

The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

Avsnitt(898)

Cybersecurity's Past, Present, and AI-Driven Future

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14 Juni 20241h 13min

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Over the past decade, usage-based pricing has soared in popularity. Why? Because it aligns cost with value, letting customers pay only for what they use. But, that flexibility is not without issues - especially when it comes to predicting revenue. Fortunately, with the right process and infrastructure, your usage-based revenue can become more predictable than the traditional seat-based SaaS model. In this episode from the a16z Growth team, Fivetran’s VP of Strategy and Operations Travis Ferber and Alchemy’s Head of Sales Dan Burrill join a16z Growth’s Revenue Operations Partner Mark Regan. Together, they discuss the art of generating reliable usage-based revenue. They share tips for avoiding common pitfalls when implementing this pricing model - including how to nail sales forecasting, adopting the best tools to track usage, and deal with the initial lack of customer data. Resources: Learn more about pricing, packaging, and monetization strategies: a16z.com/pricing-packagingFind Dan on Twitter: https://twitter.com/BurrillDanielFind Travis on LinkedIn: https://www.linkedin.com/in/travisferberFind Mark on LinkedIn: https://www.linkedin.com/in/mregan178Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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California's Senate Bill 1047: What You Need to Know

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