2024-12-12 12:00:59
风险投资公司 Dimension Capital 筹集了 5 亿美元资金，投资人工智能驱动的生命科学初创公司，反映出投资者对医疗保健和生物技术领域的人工智能应用日益浓厚的兴趣。尽管 2023 年出现下滑，但到 2024 年 12 月上旬，融资已反弹至 67 亿美元。今年的主要融资轮包括 Xaira Therapeutics 筹集超过 1B 美元、Abridge 筹集 1.5 亿美元、EvolutionaryScale 筹集 1.42 亿美元、Terray Therapeutics 筹集 1.2 亿美元。人工智能在生物技术和医疗保健领域的影响力巨大，风险投资家押注于巨大的增长潜力。此外，总部位于伦敦的 Nscale 为可持续人工智能数据中心筹集了 1.55 亿美元。

2024-12-12 12:00:00
凯西·伍德和沃伦·巴菲特是财经媒体的知名人物，他们的投资方式截然不同，但都持有亚马逊股票。随着 2025 年的临近，亚马逊似乎已准备好在人工智能、电子商务、云计算、订阅、流媒体和广告领域实现显着增长。该公司的盈利能力和强劲的现金状况使其能够对人工智能和流媒体等高增长领域进行再投资。即将推出的催化剂包括 MrBeast 主导的新流媒体系列以及对 Anthropic 的持续投资。

2024-12-12 11:05:37
WPP 已任命前 IPG 旗下麦肯世界集团 (McCann Worldgroup) 的 Elav Horwitz 为其新任执行副总裁兼战略合作伙伴关系和解决方案全球主管。Horwitz 在 McCann 工作了近九年，在 Meta 工作了六年，在将人工智能集成到创意工作流程方面拥有丰富的经验。WPP 在人工智能解决方案方面的投资包括 2024 年支出超过 3 亿美元，重点是与 Nvidia 合作，利用生成式人工智能进行 3D 广告。Horwitz 的目标是创建由人工智能驱动的以人为主导的商业解决方案，并计划与提供数据、用户体验和创造力解决方案的初创公司合作，以集成到 WPP 的基础人工智能模型 Open 中。

2024-12-12 11:05:00
I’m a Filmmaker. Ben Affleck Is Right About Artificial Intelligence | The Daily Economy 在过去的一段时间里，人工智能（AI）技术在艺术创作和创意产业中的应用引起了广泛关注。虽然有些人担心AI会取代人类艺术家的工作，但更多的人认为它将在创造力的领域带来新的可能性。演员兼制片人本·阿弗莱克最近对于这个话题发表了一些意见，他认为尽管视觉效果、声音设计、音乐等领域将会受到重大影响，但是新兴技术带来的创新和效率提升将创造更多的就业机会。 AI在艺术创作中的应用确实面临一些挑战： 1. **法律问题**：使用现有的受版权保护的材料进行训练是合法的吗？如果AI生成的作品受到了某位艺术家作品的影响，是否需要支付版税？ 2. **经济影响**：虽然旧的工作岗位可能会消失，但新的就业机会也将随之而来。例如，有人将开始开发和管理这些工具，而更多的人则会利用它们来实现创意。 3. **文化控制**：政府是否有权决定AI能够生成什么样的艺术作品？如果政府有这种权力，它可能会影响到我们文化的自由发展以及对“真理”的定义。 虽然人工智能在技术上取得了显著的进步，并且已经显示出在某些方面辅助人类创作的能力，但它仍然无法完全替代人类艺术家的独特创造力和审美判断。例如，在音乐创作中，尽管AI可以模仿特定风格的歌曲（如泰勒·斯威夫特），它却不能像真正的音乐人那样自由地融合不同流派的影响来创造出新颖而独特的声音。 总的来说，人工智能作为一种新兴技术还处于起步阶段，并且需要克服许多实际和伦理上的挑战。同时，我们必须谨慎行事以确保不损害AI工具的创新潜力，以便在未来能够继续推动艺术创作领域的进步和发展。 Unless you’ve been living under a rock for the last year, you’ve probably noticed the rapid proliferation of “Artificial Intelligence” tools. You may have noticed “AI” search results popping up on Google or Brave. Perhaps you’ve even tried software like MidJourney, ChatGPT, Claude, or Sora. These tools are often marketed as being able to do anything from help you write computer code or draw up legal contracts in seconds, to spitting out artistic masterpieces based on a simple text-based prompt. AI is frequently billed as being incredibly “disruptive”, and unsurprisingly, a lot of people have… thoughts . As a creative director and film and video producer, I do have some concerns about where this technology is going to take us, but for the most part, I think a lot of the criticism and controversy within the artist community is hysterical. So, when actor and director, Ben Affleck shared his thoughts about AI in the entertainment business with CNBC a few days ago, I was pleasantly surprised to discover that he had one of the most rational takes on the subject of any creator I’d heard talk about the issue so far. According to Affleck: “…the taste to discern and construct that is something that currently entirely eludes AI’s capability and I think will for a meaningful period of time. What AI is going to do is going to disintermediate the more laborious, less creative, and, you know, more costly aspects of filmmaking that will allow cost to be brought down, that will be lower the barrier to entry, that will allow more voices to be heard, that will make it easier for the people who want to make Good Will Huntings to go out and make it. … [W]hat costs a lot of money is now going to cost a lot less. And it’s going to hammer [the visual effects industry], and it already is. Maybe it shouldn’t take a thousand people to render something. But it’s not going to replace human beings making films. It may make your background more convincing. It can change the color of your shirt. It can fix mistakes that you’ve made. You might be able to get two seasons of House of the Dragon in a year instead of one.” 1I’ve personally spent a lot of time learning about, playing with, and even training custom Large Language Model “AI” to help me and my company produce scripts, illustrations and graphic designs, and videos more efficiently, and I am convinced that Affleck is spot on. In my layman’s understanding of the technology itself, the way Large Language Models generally function is by aggregating either the information they were initially provided in the development of the software, or new information provided by individual users.  The software then analyzes that information for patterns and commonalities which will help it pump out prose (or imagery, video, etc.) that has a high probability of meeting the user’s needs, based on an explicit text-based prompt. There are an immense number of practical uses for this kind of technology.  My company’s COO routinely uses “Generative Pre-trained Transformers” (Large Language Models which have been pre-built for software such as ChatGPT or Claude) to help draft contracts, summarize meeting notes, codify HR policies, analyze financial information, and to help with other common business tasks. But in the realm of creative production, I’ve used OpenAI’s ChatGPT software to create a few custom GPTs to function as script and screenwriting assistants for different types of projects. None of these custom GPTs actually replace my own writing, but I’ve found them to be extremely helpful to quickly get past the tyranny of the blank page.  For instance, I’ve asked my custom GPTs to help me ideate character and place names (something I absolutely hate doing) or to help me build out a coherent outline based on a stream-of-consciousness brain dump of all the ideas I have for a new story I’m trying to tell. I regularly use them to convert unformatted scripts into proper screenplays that can actually be produced and edited. I’ve used them to create image mock-ups to share with clients so we can confirm that a design brief is on the right track before investing dozens of hours on a complex illustration.  I’ve even used them to help generate dialogue options for home-brew D&D campaigns, so that the Game Master doesn’t have to come up with it on the spot.  But even with a copious amount of training, these customized GPTs absolutely cannot write a good script or create a great film or piece of visual art on their own.  There is simply no replacement for a human artist as the driver of taste and knowing what is (or isn’t) actually good .  AI mostly just spits out the average of a lot of different inputs which it has identified as being relevant to a given prompt, so what you end up with out of the box is almost always incredibly mediocre and unoriginal. Now, it’s worth noting that virtually every first draft of anything is extremely mediocre. That’s why it’s a first draft and not a final draft. The problem is, unlike human creators, AI tools don’t know how to get to the final draft. The user can keep asking AI to try again until it produces something decent, but the tool itself has no agency, no actual intelligence, and no discernment whatsoever. It won’t go back and edit its results after suddenly having a better idea. It doesn’t get a subjective feeling about what’s on trend or what is gonna pick up on some aspect of the cultural zeitgeist. It can’t draw on obscure, seemingly unrelated influences in order to come up with a brilliant mash up of something that hasn’t been done yet — and won’t, because it needs to assign most references and bits of learned information definite categories in order to meet the requirements of most prompts. For example, if you ask something like Suno to generate a song that sounds like Taylor Swift, it can do that. But what it won’t do is randomly mix subtle hints of The Beach Boys, Esquivel!, The Specials, and jazz organ virtuoso Joey DeFrancesco just because it likes aspects of those artists’ work as well. But a human songwriter will absolutely do that without even necessarily consciously thinking about it. What’s more, the human songwriter won’t just spit out the average of all those things in some mathematical way, but instead will include elements as subtle as a single chord from “God Only Knows”; orchestration similar to Esquivel’s version of “Harlem Nocturne”; a bridge inspired by the Specials’ one-drop beats and syncopated guitars; or a transposed reference to some lick DeFrancesco played on a standard like “Autumn Leaves”. As a human being, you are always going to produce art that is in some ways the amalgamation of all of your favorite influences. But your influences are specific , and while you might choose to pay homage to a single shot from a movie you love or incorporate some themes from one of your favorite books in your own writing, AI puts everything into a blender and pours out a homogenized result. There are some genuine risks with AI, of course. While I’m not really sold on the more hyperbolic claims like “AI is going to destroy the world!” it does create some really interesting legal and economic challenges.  On the legal side, the biggest concern for artists is the implications of generative AI and copyright law. It’s already difficult to sort out copyright violations in the realm of art, and there are already a number of rules — both government- and industry-defined — that determine when it is or is not acceptable to use other people’s copyrighted content or their personal likeness in a new artistic work.  AI poses new problems in the same realm: Are companies like OpenAI, Anthropic, Kuaishou, or X liable for their users’ creations? To what extent can AI models be trained on pre-existing copyrighted content? Can AI be used to recreate celebrity likenesses? Should copyright holders be paid for any AI creation that recreates their work? What if their work is merely an influence on the ultimate output? And on the economic front, Ben Affleck was absolutely correct that fields like visual effects, sound design, music, editing, and more are going to be heavily affected by all of this technology.  But like most previous periods of rapid innovation, the most likely result is going to be an explosion of new creativity and gains in efficiency — old jobs will disappear, yes, but dozens of new jobs will emerge. Meanwhile, millions of people who want to make movies or create music will (eventually) be able to create things that no one today has even dreamed of yet. These are complex problems, but it’s important to keep in mind that this is still emerging technology, and there’s a lot of work to be done before it can live up to the hype. If the government steps in and begins regulating these industries, it will almost certainly strangle innovation and the value these tools will create for everyone.  Worse, regulation will empower the government to insert itself into important questions of “trust and safety,” which — for most modern technology companies — is just another word for censorship. If the state gets to decide what art or written prose AI software can create, it captures immense power over our culture and over the very concept of truth. In my view, those are the real risks of AI. The way human artists incorporate influences and the way LLMs do it are similar processes in the abstract, but very, very different in practice, which is why they’re decent enough tools to help existing craftsmen speed up their work but a long way off of ever actually replacing human creativity…As long as we don’t do anything to destroy what’s great about these tools before they really get off the ground.

2024-12-12 11:00:00
谷歌推出第六代张量处理单元 (TPU) Trillium，标志着人工智能 (AI) 和云计算领域的重大进步。主要功能包括卓越的性价比、卓越的可扩展性、先进的硬件创新、与 Google Cloud 生态系统的无缝集成，以及与 Gemini 2.0 和 Deep Research 等未来人工智能发展的结合。AI21 Labs 等早期采用者报告在成本效率和可扩展性方面取得了显着改进。Trillium 面临着来自 NVIDIA 和亚马逊的竞争，但如果它能够通过谷歌云之外的性能验证和生态系统兼容性证明其价值，则有潜力吸引寻求优化人工智能解决方案的企业。谷歌

2024-12-12 11:00:00
一位作家在遛狗时使用人工智能制定家庭膳食计划，体验到了突破，意识到人工智能可以多么有效地处理繁琐的任务。尽管最初在将人工智能融入日常生活方面遇到了困难，但作者通过简单的请求找到了成功和生产力，这表明人们应该在担心存在问题之前探索人工智能在生活中的实际用途。随着人工智能技术的迅速发展，本文鼓励读者拥抱其实用性，同时注意潜在的更广泛的影响。

2024-12-12 10:25:00
SoundHound AI 的股价自 1 月份以来已飙升超过 600%，市值超过 50 亿美元。在英伟达投资后，它的受欢迎程度有所提高，但面临着成本管理、无需收购的有机增长以及改善现金流方面的挑战。尽管同比增长令人印象深刻，但季度与季度的比较凸显了其对收购的依赖。随着经营亏损上升和大量现金消耗，该公司可能需要在 2025 年发行更多股票，这可能会稀释股票价值。除非 SoundHound 解决这些问题，否则建议投资者对明年购买该股票保持谨慎。

2024-12-12 10:22:28
人工智能正在改变 IT 格局，改变企业竞争和应对挑战的方式。其最重要的影响是通过系统监控和网络管理等重复任务的自动化，提高效率并减少错误。人工智能还通过实时检测和响应威胁来增强网络安全，在技术驱动的环境中保护数据。此外，人工智能驱动的分析使组织能够从大型数据集中提取有价值的见解，以进行战略决策和预测绩效分析，从而促进创新并保持竞争优势。

2024-12-12 10:00:00
由于对其人工智能平台的强劲需求，Palantir Technologies 的股价今年已飙升超过 400%，但分析师预测存在潜在的下行风险，中位价格目标意味着较当前水平下降 48%。相比之下，Shopify 和 Arm Holdings 被视为更具吸引力的投资选择。Loop Capital将Shopify的目标上调至每股140美元，表明其市值为1800亿美元，而摩根士丹利则预测Arm的市值可能达到1830亿美元，目标价为每股175美元。两家公司在人工智能领域都提供了引人注目的机会，尽管目前估值较高，但预计未来几年收入将出现大幅增长。股份帕兰提尔科技

2024-12-12 09:44:54
2024 年第四季度，全球人工智能市场规模达到 6382.3 亿美元，在医疗保健、金融、零售和网络安全等行业广泛采用的推动下，预计到 2034 年将增长至 3.6 万亿美元。大约 83% 的公司将人工智能视为战略重点，因为它具有创新和效率的潜力。“AI 双胞胎”的概念越来越受欢迎，Twin Protocol 等平台使个人能够创建数字伴侣来管理任务并提供个性化支持。这些数字孪生使用机器学习和区块链技术来维护用户代理和数据隐私，同时在各个行业提供应用程序。人工智能的未来有望带来变革性的合作伙伴关系，将个人能力扩展到不同领域。