From the morning post and our Live Member Chat Room:
IBM, on the other hand, is rolling out a new type of AI chip (AIU) that is supposed to be 10 times faster with 1/10th the power consumption of standard chips. We don’t have all the IBM specs yet but, here’s a quick comparison to NVDA:
🤓 IBM’s AIU and Nvidia’s AI chips are both designed to accelerate deep learning tasks, but they have some differences in their features and performance. Here are some of the main points of comparison:
- Precision: IBM’s AIU uses approximate computing and supports a range of smaller bit formats, including both floating point and integer representations, to reduce the amount of computation and memory required for AI operations. Nvidia’s AI chips use tensor cores that can perform mixed-precision calculations, such as FP16 and FP32, to boost the speed and accuracy of AI models.
- Speed: IBM’s AIU can perform up to 1.5 trillion operations per second, while Nvidia’s latest AI chip, the H100, can perform up to 2.5 trillion operations per second. However, the speed of an AI chip also depends on other factors, such as memory bandwidth, cache size, and interconnects.
- Power: IBM’s AIU claims to use 10 times less power than a CPU for deep learning tasks, while Nvidia’s H100 claims to use 3 times less power than a CPU for the same tasks. The power consumption of an AI chip also depends on the workload, the cooling system, and the system configuration.
- Price: IBM did not provide a specific price for the AIU, but it was expected to be available in the first half of 20221. However, due to the global chip shortage and supply chain disruptions caused by the pandemic, the launch of the AIU was delayed until the third quarter of 20232. Nvidia did not provide a specific price for the H100 either, but it was estimated to cost somewhere between $20,000 and $30,0003.
- Compatibility: IBM’s AIU is designed to be as easy to use as a graphics card, and can be plugged into any computer or server with a PCIe slot2. It is also compatible with IBM’s cloud and hybrid cloud platforms, as well as with popular open-source frameworks such as TensorFlow and PyTorch2. Nvidia’s H100 is also compatible with various cloud platforms and frameworks, but it requires a special socket called NVLink that is only available on Nvidia’s own DGX systems or servers from select partners3.
We’ve been hoping to catch IBM on a dip but we haven’t had one recently. I do love that company!
Then I asked Claude(AI) for his analysis:
- Sell 10 IBM 2025 $135 puts at $10 ($10,000)
- Buy 20 IBM 2025 $140 calls at $16.50 ($33,000)
- Sell 15 IBM 2025 $160 calls at $8 ($12,000)
- Sell 7 IBM Nov $145 calls at $4.60 ($3,220)
That’s net $7,780 on the $40,000 spread so we have $32,220 (414%) of upside potential at $160 and, along the way, we’ve used 87 out of 514 days so far so at least 5 more sales of $3,000 can drop another $15,000 into our pockets while we wait.
👺Here is my analysis of IBM based on the recent articles:
– IBM delivered solid Q2 results, beating on EPS but slightly missing on revenue. The company maintained its full-year guidance for revenue growth of 3-5% and $10.5B in free cash flow.
– IBM’s portfolio shift towards higher growth software and consulting is paying off. These segments drove revenue in Q2 and saw strong profitability expansion. The mainframe cycle is also benefiting software revenue.
– New AI offerings like Watson X are gaining traction, evidenced by strong growth in IBM’s data/AI consulting practice. Monetization will take time but IBM is well positioned in enterprise AI.
– The acquisition of Apptio boosts IBM’s hybrid cloud capabilities. It provides a platform to optimize IT spend across cloud environments. Apptio’s $450B of benchmarking data offers future AI monetization potential.
– IBM’s turnaround is progressing but gradual. Revenue growth remains in the 3-5% range and the dividend increases are small. But the foundations are solidifying with stronger profitability and cash generation.
– Valuation is reasonable at 15x forward earnings given IBM’s stable free cash flow and 4.5% dividend yield. But growth catalysts are still needed to re-rate the multiple significantly higher.
– Technically, the chart shows a potential double bottom forming. A breakout above $148 could signal renewed momentum. But more range-bound action seems likely near-term.
Overall, IBM is making steady progress as a “show me” turnaround story. The foundations are improving but growth needs to accelerate for meaningful upside. At current valuations, IBM offers a reasonable value play with solid income.