{"id":3065,"date":"2023-07-05T19:55:29","date_gmt":"2023-07-05T19:55:29","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2023\/07\/05\/nvidia-ceo-european-generative-ai-execs-discuss-keys-to-success\/"},"modified":"2023-07-05T19:55:29","modified_gmt":"2023-07-05T19:55:29","slug":"nvidia-ceo-european-generative-ai-execs-discuss-keys-to-success","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2023\/07\/05\/nvidia-ceo-european-generative-ai-execs-discuss-keys-to-success\/","title":{"rendered":"NVIDIA CEO, European Generative AI Execs Discuss Keys to Success"},"content":{"rendered":"
\n

Three leading European generative AI<\/a> startups joined NVIDIA founder and CEO Jensen Huang this week to talk about the new era of computing.<\/p>\n

More than 500 developers, researchers, entrepreneurs and executives from across Europe and further afield packed into the Spindler and Klatt, a sleek, riverside gathering spot in Berlin.<\/p>\n

Huang started the reception by touching on the message he delivered Monday at the Berlin Summit<\/a> for Earth Virtualization Engines (EVE), an international collaboration focused on climate science. He shared details of NVIDIA\u2019s Earth-2 initiative<\/a> and how accelerated computing, AI-augmented simulation and interactive digital twins drive climate science research.<\/p>\n

Before sitting down for a fireside chat with the founders of the three startups, Huang introduced some \u201cspecial guests\u201d to the audience \u2014 four of the world\u2019s leading climate modeling scientists, who he called the \u201cunsung heroes\u201d of saving the planet.<\/p>\n

\u201cThese scientists have dedicated their careers to advancing climate science,\u201d said Huang. \u201cWith the vision of EVE, they are the architects of the new era of climate science.\u201d<\/p>\n

Taking on Formidable Forces<\/strong><\/h2>\n

\u201cThere is an enormous amount of AI startups in Germany, and I\u2019m delighted to see it,\u201d Huang said. \u201cYou\u2019re in a brand-new computing era, and when that happens, everybody\u2019s on square one.\u201d<\/p>\n

Huang welcomed to the stage the founders from Blackshark.ai, Magic and DeepL. Planetary management, artificial general intelligence, or AGI, and language translation are some ways the startups use generative AI.<\/p>\n

    \n
  • Blackshark.ai uses AI and hyperscaling distributed spatial computing to turn 2D images into data-rich 3D worlds.<\/li>\n
  • Magic is building an AGI software engineer, enabling small teams to write code significantly faster and more cheaply.<\/li>\n
  • DeepL aims to help everything communicate with everybody else with its AI-powered translation tool.<\/li>\n<\/ul>\n

    All three companies make solutions that could be seen as going up against products from established companies.<\/p>\n

    \n

    \"\"

    An audience of more than 500 attended the fireside chat.<\/figcaption><\/figure>\n

    \u201cWhy did you take on such formidable forces?\u201d Huang asked the founders.<\/p>\n

    Blackshark co-founder and CEO Michael Putz shared that the startup\u2019s product is similar to what you might see in Google Earth.<\/p>\n

    But Blackshark claimed its coverage of the planet is 100%, compared to Google Earth\u2019s 20%. And while Google might take a few months to update parts of its map, Blackshark only needs three days, Putz said.<\/p>\n

    Magic co-founder, CEO and AI lead Eric Steinberger explained how his company is trying to build an AGI AI software engineer that will work as though it were a team of humans.<\/p>\n

    He said it\u2019ll remember conversations from months ago and can be messaged via an app like any other engineer. Rather than creating an alternative to existing solutions, Magic sees itself as trying to build something categorically different.<\/p>\n

    \u201cIt\u2019s hard to build, but if we can get it right, we\u2019re in an even playing field, even up against the giants,\u201d said Steinberger.<\/p>\n

    DeepL founder and CEO Jaroslav Kutylowski said his company\u2019s work was initially an intellectual challenge. \u201cCould they do better than Google?\u201d the team asked themselves. To Kutylowski, that sounded like fun.<\/p>\n

    Intuition, Efficiency and Resilience<\/strong><\/h2>\n

    Steinberger got a chuckle from the audience as he asked Huang about his decision-making process in driving NVIDIA forward. \u201cYou\u2019re right, either always or almost always. How do you make those decisions before it\u2019s obvious?\u201d<\/p>\n

    \u201cThat\u2019s a hard question,\u201d Huang responded.<\/p>\n

    Huang talked about the intuition that comes from decision-making, saying, in his case, it comes from life and industrial experience. In NVIDIA\u2019s case, he said it comes from having a lot of ideas \u201ccooking\u201d simultaneously.<\/p>\n

    He explained that with the invention of the GPU, the intention was never to replace the CPU but to make the GPU part of the next great computer by taking a full-stack approach.<\/p>\n

    With data centers and the cloud, Putz asked for advice on the best approach for startups when it comes to computing.<\/p>\n

    NVIDIA joined the \u201cfabless semiconductor\u201d industry, where there was very little capital required for a factory to funnel resources into R&D teams of 30-50 engineers instead of 500 like a more traditional semiconductor company.<\/p>\n

    Today, Huang explained, with the software 2.0 generation, startups can\u2019t spend all their money on engineers \u2014 they need to save some to prototype and refine their software.<\/p>\n

    And it\u2019s important to use the right tools to do the work for cost-efficient workloads. A CPU might be cheaper than a GPU per instance, but running a workload on a GPU will take \u201c10x less time,\u201d he said.<\/p>\n

    Kutylowski asked about the most significant challenges NVIDIA and Huang have faced along the company\u2019s 30-year journey.<\/p>\n

    \u201cI go into things with the attitude of, \u2018How hard can it be? Well, it turns out it\u2019s super hard,\u201d Huang answered. \u201cBut if somebody else can do it, why can\u2019t I?\u201d<\/p>\n

    The answer includes the right attitude, self-confidence, the willingness to learn, and not setting an expectation of perfection from day one, he said. \u201cBeing resilient as you fail to the point where you eventually succeed \u2014 that\u2019s when you learn,\u201d Huang said.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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