Nvidia Stock Price Forecast

Nvidia’s stock is perhaps the superstar performer of the NASDAQ and S&P in 2023. Its stock price has leapt as you can see in the price chart below yet investors wonder if this bullish run will continue.

The outlook for 2024 and next 5 years is still positive, however over the next 3 to 6 months, we might see a backoff from investors in chip stocks and AI stocks.

Nvidia, MicroChip Tech, Qualcomm, Broadcom, Texas Instrument, Intel and AMD have blossomed on the promise of the AI boom. It’s happening now due to a convergence of political, economic, and technology factors. Corporations are pouring money into AI software development including AI stock forecasting solutions for investors, after the successful launch of ChatGPT.

Top performing microchip companies.
Top performing microchip companies. Screenshot courtesy of Barchart.

For corporations, AI and chips have more to do with labor savings, although they serve everything from recruiting apps to stock forecasting to cloud computing. The hope too on a practical basis, is that AI automation can replace millions of high paid and low paid workers, and solve the unsolvable skilled worker shortage. And there is hope that customer service and consumer satisfaction might grow.

Yet, AI can also be used to create opportunities and jobs. Politicians will decide which way that goes.

Current NVDA Stock Price

CNN Business’s 45 market analysts provide their 12-month price forecasts for NVIDIA Corp with a median target of 460.00, high estimate of 600.00 and a low projection of 175.00.  Their forecasters predict earnings per share for the coming Q3 period from 74 cents to $2.68.   36 analysts call to buy, while 8 evaluate it as an outperformer.

Nvidia’s chips are made by Taiwan Semiconductor which has also popped in price this year. Apple and AMD also buy their microchips.  In 2024, the current battle between Taiwan and China, could threaten Nvidia’s supply chain. Combine that with a potential economic slide for the next 12 months, and we might want to be cautious about NVDA stock. If you’re a long term investor, confident in a status quo situation internationally, then NVDA still might be one of the best bets for the next 5 years.

Is AI Enough to Support the Chipmakers?

Certainly AI will support increased GDP per worker given fewer workers and higher production, along with presumably improve processes in every area of business. So the promise of AI is there for the corporations. How small businesses will access and leverage the advantage still isn’t well understood. We have to have faith that AI will be leveraged by small business.

Stocks like NVDA are driven by the relentless, progressive demands of artificial intelligence processing.  A higher grade and faster processing speed are required, and companies such as Nvidia are the masters in this category.  In fact, Nvidia has always had a reputation of innovation and being ahead of the market with respect to graphics chips.  It’s their expertise in graphics optimization that made them leaders in the new AI chip realm.

Here are 7 Reasons why Nvidia is a leader in the AI chip competition:

  1. GPU Technology: NVIDIA pioneered the use of Graphics Processing Units (GPUs) for general-purpose computing, including AI. GPUs excel at parallel processing, which is crucial for deep learning algorithms that underpin many AI applications. NVIDIA’s GPUs are highly efficient and capable of handling large-scale data processing, making them ideal for training and deploying AI models.
  2. CUDA Architecture: NVIDIA developed CUDA (Compute Unified Device Architecture), a parallel computing platform and programming model. CUDA allows developers to harness the power of NVIDIA GPUs and accelerate AI and other computationally intensive workloads. Its wide adoption has contributed to NVIDIA’s dominance in the AI space.
  3. Deep Learning Frameworks: NVIDIA actively supports and collaborates with major deep learning frameworks like TensorFlow, PyTorch, and Caffe. They optimize these frameworks to run efficiently on their GPUs, enabling faster training and inference for AI models. NVIDIA’s involvement in the development and optimization of these frameworks has made it easier for researchers and developers to utilize AI technologies.
  4. Hardware Innovations: NVIDIA has continuously pushed the boundaries of hardware innovation. They introduced specialized hardware accelerators like Tensor Cores in their GPUs, which deliver dedicated matrix multiplication capabilities and significantly enhance AI performance. NVIDIA’s focus on developing specialized hardware for AI has led to the creation of powerful and efficient solutions for training and inference tasks.
  5. AI Ecosystem: NVIDIA has built a comprehensive ecosystem around AI. They provide software development kits (SDKs), libraries, and tools that streamline AI development and deployment. Their platform, NVIDIA AI Enterprise, offers solutions for AI infrastructure, data center management, and application deployment, catering to the needs of enterprises adopting AI technologies.
  6. AI Market Dominance: NVIDIA’s GPUs have become the de facto standard for AI research and implementation. Many organizations, including tech giants, research institutions, and startups, rely on NVIDIA’s hardware and software solutions for their AI initiatives. The widespread adoption of NVIDIA’s technology has solidified its position as a leader in the AI era.
  7. Continuous Innovation: NVIDIA’s commitment to innovation is evident in their ongoing research and development efforts. They continue to introduce new products and technologies tailored for AI workloads. For example, NVIDIA’s recent advancements include the launch of the Ampere architecture, which delivers significant performance improvements for AI tasks, and the introduction of the NVIDIA A100 Tensor Core GPU, designed specifically for AI and high-performance computing.

Of course, the company is well capable of introducing new innovations to gain more marketshare, which investors are well aware of.

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