Humans will still play a crucial role — but instead of assembling parts or operating machinery, they will maintain robots and keep them running.

In these future factories, robots coordinate in unison, completing work automatically — without breaks, every hour of the day — to get products out the door. 

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While Nvidia initially developed its graphics processing units (GPUs) for gaming, these chips turned out to be ideal for powering AI tasks. Now, the company is focusing its efforts on providing the computing hardware — notably its A100 and H100 GPUs — and the software infrastructure required for developing generative AI applications.

Amid the generative AI rush, Nvidia has grown rapidly. In fact, it recently surpassed Microsoft and Apple to become the world’s most valuable company. To bolster its leadership position and keep ahead of AI computing competitors like AMD and Intel, Nvidia has forged relationships with companies across the AI landscape.

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While most genAI initiatives are still in early stages of development, incumbents and startups are betting heavily on its potential.

ABB, for instance, has identified over 100 internal applications for the tech, from robotics to predictive maintenance. Retrocausal, which develops a computer vision-enabled AI copilot for the assembly line, estimates that genAI can reduce manual assembly time by a third.

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Driving the upswing: Humanoid robot funding has reached a record annual level just 4 months into the year, while investment in the operational technology (OT) security tools that can help protect them has already outpaced the previous 2 years combined.

Despite the gains, sector-wide deal count fell to its lowest quarterly level since 2016. This mirrors the broader pullback in venture dealmaking globally. 

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The company has faced multiple high-profile incidents over the past 6 years — including crashes involving its planes and a fuselage blowout. This series of events has resulted in a decline in consumer trust, aggravated airlines, and lost sales to rival Airbus.

Amid these challenges, Boeing has shaken up its corporate leadership and moved to improve its manufacturing quality. For instance, the company is exploring a reintegration with Spirit AeroSystems to help address production flaws.

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Large language models (LLMs) are enabling new capabilities with simulation and generative design, empowering humanoid robots, and paving the way for copilots to improve productivity across manufacturing, sales, and the aftermarket.

With the growing focus on software-defined, electric vehicles, and as automakers look to build a more digital-forward car buying experience, these technologies are growing increasingly relevant.

Using the CB Insights technology intelligence platform, we analyzed signals such as funding, analyst briefings, business relationships, headcount growth, Mosaic scores, and more to identify 15 high-momentum technologies that auto stakeholders should be watching in 2024.

Our 19-page report digs into trends like:

• AI and quantum computing are accelerating vehicle development and reducing R&D costs, allowing OEMs to introduce new designs, prototypes, and materials.
• Automotive production will see gains from more sophisticated robotics and automation solutions, laying the groundwork for cost-effective, modular production of next-generation vehicles.
• AI is enabling a more personalized, efficient automotive sales process, with new fintech solutions and engagement tools speeding up the sales cycle and improving accessibility for car buyers.
• Connected vehicle technology is enabling real-time visibility into vehicle health and security, providing OEMs with valuable data to enhance other facets of the value chain and the in-vehicle experience.
• Chatbots and computer vision-led inspection solutions are driving efficiencies in vehicle repair, improving service desk productivity and technician accuracy.

And much more. Download the full report to see them all.

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A handful of developers are targeting 2024 to release their humanoid robots, which are designed to perform tasks similar to humans. Technologies like generative AI and reinforcement learning are helping drive this progress. However, the impact will be limited at first, and it will likely take 3-5 years to see more widespread commercial rollout and usefulness.

Below, we dive into 6 industries that humanoids will impact the most in both the near- and long-term, as well as the technology firms making this possible:

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The company maintains a robust internal combustion portfolio, but it has aggressively invested across the entire vehicle electrification ecosystem. Despite scaling back its EV production goals to account for fluctuating consumer demand, GM remains committed to electric vehicles and plans to have the capacity to produce 1M EVs by 2025.

Meanwhile, GM has also pulled back from fully autonomous driving by reducing spending on Cruise — its autonomous vehicle (AV) subsidiary — and moved investments away from AV companies. However, the company has retained its focus on its advanced driver assistance system (ADAS), Super Cruise.

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AI cuts across practically every emerging area of activity. For instance, on-demand manufacturing companies are using AI to automatically match clients with vendors, while manufacturing analytics platforms use it to generate real-time insights from factories and process plants.

Early-stage companies in these areas focus on a range of manufacturing industries, including aerospace, automotive, consumer products, oil & gas, pharmaceuticals, and semiconductors.

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However, as deal sizes have gotten smaller, the space has seen a corresponding shift toward early-stage dealmaking. In 2023, 69% of climate tech deals went to early-stage companies — an increase of 14 percentage points vs. 2022.

Using CB Insights data, we break down the climate tech landscape and the markets and startups seeing the most traction.

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2024 is set to see the commercial release of several new humanoid robots, which resemble the human body and can perform tasks traditionally carried out by humans in areas like manufacturing, logistics, and retail.

The surge is propelled by advancements in AI, pilot programs demonstrating commercial viability, and significant investment from big tech. In particular, robotics developers are targeting more realistic human-robot interactions using large language models (LLMs) and natural language processing.

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This 77% drop brought advanced manufacturing funding to its lowest quarterly level since 2018.

However, deal count largely remained level for the second straight quarter.

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New possibilities have emerged thanks to the proliferation of satellite launches — with SpaceX alone conducting a record 98 launches during 2023 — combined with the affordability of drones and advancements in imaging technologies.

This progress opens opportunities for startups and incumbents, helping expand geospatial use cases and capabilities across industries like agriculture, automotive, construction, defense & national security, insurance, manufacturing, mining, oil & gas, and more.

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These robots resemble the human form and are designed to be multi-talented, making it possible to swap them in for complex tasks normally handled by flesh-and-bone employees. Popular robot forms like automated guided vehicles (AGVs) & autonomous mobile robots (AMRs) and collaborative robotic arms are much less flexible.

However, humanoid robots are complicated to build and deploy. They require substantial sensor processing, advanced control, and complex skill execution. They also need multimodal artificial intelligence (AI) to understand the environment around them.

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The company first introduced electric vehicles (EVs) in 2013 with its i3 vehicle. Since then, the automaker has continued to leverage investments and partnerships to develop its EV models as well as pursue its ambitions in autonomous vehicles, such as via its collaboration with NVIDIA.

Looking ahead, BMW is aiming to introduce solid-state batteries in vehicles after 2025, a leap forward in battery technology that is expected to bring down the costs of EVs while also increasing their range. The company is leaning on investments and partnerships with companies like Solid Power to reach that goal. Further, the automaker is building its expertise in areas like grid tech to help support the rollout of electric vehicles.

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At the heart of its growth strategy is the integration of AI. In 2017, the company founded the Bosch Center for Artificial Intelligence — a global team dedicated to advanced AI research — while investing over $100M+ into a new AI campus. The company’s 2025 goal is to incorporate AI in all of its products or develop them using AI.

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However, 3D printing adoption has been slower than anticipated, accounting for just 0.1% of the total value of manufacturing output today.

Instead of mass production, manufacturers have been using it for applications like rapid prototyping or the production of components with unique geometries that are otherwise impossible to create with more traditional methods.

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There are multiple reasons behind the swelling tide. For one, chips are an integral — and growing — component of devices across sectors, from consumer products to automotive to industrial IoT.

Geopolitics also play a major role. Many countries want to ensure self-sufficiency in an industry they see as being foundational to economic growth and national security.

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Historically, uptake of reusable packaging has been slow due to logistical complexities, affordability, and worries about customer adoption. However, consumers are also ready for a switch: A 2023 pilot study conducted by the WWF found that one-third of consumers opt for reusable packaging when given the option. 

It’s important to note that for reusable packaging to actually be sustainable, companies need to ensure its return and reuse. For instance, plastic reusable packaging typically needs to be used 50+ times before its environmental impact outperforms paper packaging.

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Research & development (R&D) productivity has steadily declined over the past century, which means businesses must spend more on R&D to keep technological advancement moving forward. The manufacturing sector alone accounts for over half of total R&D investment in the US, according to the National Science Foundation. 

However, an emerging set of technologies — ranging from augmented reality design tools to quantum computing simulations — offers manufacturers an opportunity to reduce costs and drive efficiencies in product design and development.

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This surge was driven by multiple billion-dollar deals to sustainability-focused industrial tech players. A global push among governments to invest in areas like clean energy has helped ignite private investor enthusiasm.

Using CB Insights data, we assess the landscape for advanced manufacturing technologies. Below, we cover:

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