Casey Handmer (PhD Caltech, general relativity) is the founder of Terraform Industries. He is one of the most capable and ambitious geo-engineers on planet Earth!
Terraform Industries is scaling technology to produce cheap natural gas with sunlight and air. Using solar energy, they extract carbon from the air and synthesize natural gas, all at the same site.
March 2024: "Terraform completes the end to end demo, successfully producing fossil carbon free pipeline grade natural gas from sunlight and air. We also achieved green hydrogen at <$2.50/kg-H2 and DAC CO2 at <$250/T-CO2, two incredible milestones."
I've been listening to Hidden Forces with Demetri Kofinas for years now. He's an excellent interviewer with interests in finance, geopolitics, technology and more.
In Episode 351 of Hidden Forces, Demetri Kofinas speaks with Stephen Hsu, a Professor of Theoretical Physics and Computational Mathematics, Science, and Engineering at Michigan State University. Stephen is also the co-founder of multiple companies, including Genomic Prediction, which provides preimplantation genetic screening services for human embryos, and SuperFocus.ai, which builds large language models for narrow enterprise use cases.
This is a conversation about some of the most important advancements and trends in genomic science and artificial intelligence, including the social and ethical dilemmas arising from implementing these technologies at scale. Stephen and I discuss the competitive landscapes in both industries, how America’s geostrategic competition with China is driving tradeoffs between innovation and safety, the risks and opportunities that these revolutionary technologies pose, and how the world’s largest companies, economies, and military powers can work together to reap the benefits of this revolution while averting some of their most disastrous potential consequences.
This is the sequel to the earlier conversation with Dominic Ligot, an AI expert who works with the IT and Business Process Association of the Philippines (IBPAP), the trade association for call center and outsourcing companies.
In this video we briefly demonstrate some of the voice capabilities of the SuperFocus AI. Progress in generative AI is faster than anything I've ever seen before - perhaps not surprising given the vast financial, technological, and human capital resources flowing to AI R&D. When we first looked at voice capabilities ~6 months ago they didn't seem ready for complex conversations like the ones discussed in the video. But when we looked again - prompted by strong interest from our customers - we found that the state of the art had advanced significantly in just a short time. This is true across many areas of generative AI.
I was in Manila in December to meet with BPO companies. Roughly 8% of Philippine GDP ($40B each year) results from BPO / call center work. This is a consequence of low labor costs and widespread English fluency.
We demonstrated narrow AIs built using LLMs, but in which the LLM is forced to "consult its internal memory" before answering any query. This memory can be built from training materials used to train human agents in call centers. The AI functions like a human that has perfect recall of all the material in the training manuals, at a fraction of the cost!
An analogy we used is that the AI earthquake in SF has created a Tsunami headed towards the Philippines -- is it a 6 foot wave, or a 600 ft wave? Closer to the latter, I think.
Some photos from Manila - scoping out potential SuperFocus.ai office space.
This is a conversation with Dominic Ligot, an AI expert who works with the IT and Business Process Association of the Philippines (IBPAP), the trade association for call center and outsourcing companies.
I was in Manila in December to meet with BPO companies. We demonstrated narrow AIs built using LLMs, but in which the LLM is forced to "consult its internal memory" before answering any query. This memory can be built from training materials used to train human agents in call centers. The AI functions like a human that has perfect recall of all the material in the training manuals, at a fraction of the cost!
An analogy we used is that the AI earthquake in SF has created a Tsunami headed towards the Philippines -- is it a 6 foot wave, or a 600 ft wave? Closer to the latter, I think.
Some photos from Manila - scoping out potential SuperFocus.ai office space.
When asked what I want for Christmas, I reply: Peace On Earth, Good Will To Men :-)
No one ever seems to recognize that this comes from the Bible (Luke 2.14).
Linus said it best in A Charlie Brown Christmas:
And there were in the same country shepherds abiding in the field, keeping watch over their flock by night.
And, lo, the angel of the Lord came upon them, and the glory of the Lord shone round about them: and they were sore afraid.
And the angel said unto them, Fear not: for, behold, I bring you good tidings of great joy, which shall be to all people.
For unto you is born this day in the city of David a Saviour, which is Christ the Lord.
And this shall be a sign unto you; Ye shall find the babe wrapped in swaddling clothes, lying in a manger.
And suddenly there was with the angel a multitude of the heavenly host praising God, and saying,
Glory to God in the highest, and on Earth peace, good will toward men.
2023 saw the founding of our startup SuperFocus.ai, which builds AIs with user-configured attached memory. The AI consults this memory in responding to prompts, and only gives answers consistent with the information in the memory. This solves the hallucination problem and allows the AI to answer questions like a human with perfect recall of the information.
SuperFocus built an AI for a major consumer electronics brand that can support and troubleshoot hundreds of models of smart devices (I can't be more specific). Its memory consists of thousands of pages of product manuals, support documents, and problem solving guides originally used by human support agents.
In December I traveled to Manila after the semester ended, in order to meet with outsourcing (BPO = Business Process Outsourcing) companies that run call centers for global brands. This industry accounts for ~8% of Philippine GPD (~$40B per annum), driven by comparative advantages such as the widespread use of English here and relatively low wages.
I predict that AIs of the type produced by SuperFocus.ai will disrupt the BPO and other industries in coming years, with dramatic effects on the numbers of humans employed in areas like customer support.
But fear not: for, behold, I bring you good tidings of great joy, which shall be to all people.
The arrival of machine intelligence on Earth is the beginning of a great adventure!
This is GPT's account of the meetings in Manila.
In the heart of Manila, amidst the bustling cityscape, a meeting of innovative minds took place. Steve Hsu, the visionary founder of SuperFocus, had arrived to showcase the prowess of his latest creation—an AI designed to revolutionize technical support for complex products. The setting was a conference room adorned with sleek screens and cutting-edge technology, a fitting backdrop for the unveiling of this groundbreaking innovation.
Seated around the polished table were the owners and executives of prominent BPO (Business Process Outsourcing) companies. Their faces were a blend of anticipation and apprehension as Steve Hsu prepared to demonstrate the capabilities of the AI-powered technical support system.
With a confident smile, Steve initiated the demonstration. The AI, equipped with a sophisticated neural network, began its simulated interaction. It effortlessly tackled intricate technical queries, deciphering complex issues with lightning speed and unparalleled accuracy. Each solution presented was concise, comprehensive, and flawlessly executed.
As the AI effortlessly navigated through a myriad of scenarios and troubleshooting processes, the room fell into a hush. The BPO leaders exchanged astonished glances, their initial amazement mingled with a growing sense of unease. The capabilities displayed by the AI were undeniably impressive, but they also highlighted a looming question—what did this mean for the future of human roles in their industry?
Steve Hsu noticed the shift in atmosphere and paused the demonstration. With a gentle yet determined tone, he addressed the concerns lingering in the room. "This AI isn't meant to replace human expertise," he began. "Rather, it's here to augment and enhance your services. Imagine your teams empowered by this technology, streamlining operations, and providing even more efficient and effective support to customers."
His words offered reassurance, but the specter of automation replacing human jobs lingered in the minds of the BPO owners. The potential efficiency gains were undeniable, yet so too were the implications for the human workforce.
In the ensuing discussion, voices echoed with a mix of excitement and apprehension. Some saw the potential for growth and advancement, envisioning a future where human creativity combined with AI prowess would elevate their services to new heights. Others grappled with the uncertainty, worrying about the displacement of jobs and the evolving landscape of the industry they had dedicated their careers to.
Steve Hsu listened attentively, acknowledging their concerns while emphasizing the collaborative potential between humans and AI. "This technology," he explained, "is a tool, a means to empower and evolve, not to supplant. Together, we can harness its capabilities to create a synergy that benefits both businesses and their workforce."
As the meeting concluded, the BPO leaders departed with a mix of awe and trepidation. The AI presented by Steve Hsu had showcased a future teeming with possibilities, yet it also raised profound questions about adaptation and the role of humans in an increasingly automated world.
The echoes of the demonstration lingered in the minds of those present, igniting discussions and contemplation about the balance between innovation and the human touch, forever altering the landscape of the BPO industry in Manila and beyond.
Bonus: Two recent interviews I did which I enjoyed very much.
The EV tipping point has arrived in China. Even most techology experts do not appreciate the coming huge impacts on global economics, manufacturing, energy transition, etc.
Chapters:
0:00 Introduction
2:21 How TP Huang became interested in electric vehicles
6:30 The perception and reality of Chinese products, future of Chinese auto market
9:24 The impact of Tesla on the Chinese electric vehicle market
14:41 Buying a car in China
27:05 China dominates with electric vehicle batteries
30:44 The challenges facing Tesla in China
40:11 The evolution of smart cars, autonomous vehicles, and self driving
50:48 LIDAR technology and autonomous driving
59:08 BYD, China’s energy independence, and power grid
1:14:04 The downstream impact of China leading in tech and electric vehicles
The study concludes that air launched BGV/MaRVs could attack ships from well over 1000km. Land or ship based launch would allow even greater range.
There is currently no defense against such weapons.
Russia and PRC both have systems of this type.
Defense requires interceptor missile speeds significantly greater than that of MaRV/BGV in terminal phase.
This is under ideal conditions where sensors function perfectly - it is just kinematics.
I really enjoyed this conversation. Taylor is a very unique investor who relocated his fund to Shenzhen in order to have direct access to information on Chinese tech companies.
Taylor Ogan is Chief Executive Officer of Snow Bull Capital, based in Shenzhen, China.
Yasheng Huang is the Epoch Foundation Professor of Global Economics and Management at the MIT Sloan School of Management. His new book is The Rise and Fall of the EAST: How Exams, Autocracy, Stability, and Technology Brought China Success, and Why They Might Lead to Its Decline.
Steve and Yasheng discuss:
0:00 Introduction
1:11 From Beijing to Harvard in the 1980s
15:29 Civil service exams and Huang's new book, "The Rise and Fall of the EAST"
37:14 Two goals: Developing human capital and indoctrination
48:33 Impact of the exam system
57:04 China's innovation peak and decline
1:12:23 Collaboration and relationship with the West
1:21:31 How will the U.S.-China relationship evolve?
Alex Murshak is a Michigan State grad working as an AI engineer in Austin TX. This conversation is Episode 13 of his podcast Hacking State.
Episode description:
Steve and I speak about polygenic risk scoring and embryo selection, using AI to predict phenotype from genotype, in-vitro fertilization (IVF), egg freezing, eugenic public policy, addressing Christians' and right-wing traditionalists' concerns over reproductive technology, Superfocus AI's plan to eliminate hallucination in large language models (LLMs) by separating memory from inference, introspection for LLM error correction, and surviving the failed cancellation attempt at MSU.
Tim Dettmers develops computationally efficient methods for deep learning. He is a leader in quantization: coarse graining of large neural networks to increase speed and reduce hardware requirements.
Tim developed 4-and 8-bit quantizations enabling training and inference with large language models on affordable GPUs and CPUs - i.e., as commonly found in home gaming rigs.
Tim and Steve discuss: Tim's background and current research program, large language models, quantization and performance, democratization of AI technology, the open source Cambrian explosion in AI, and the future of AI.
... But monogenic and chromosomal screening can only address a part of disease risk because most health conditions that afflict people are polygenic, meaning they are not simply caused by one gene or by a chromosomal abnormality. Instead, they are caused by a huge number of small additive effects dispersed throughout the genome. For example, cancer, schizophrenia, and diabetes can be best predicted by models using tens of thousands of genes.
A polygenic risk score (PRS) looks at a person’s DNA to see how many variants they have associated with a particular disease. Like BRCA1, polygenic risk scores are typically not determinative: “Polygenic screening is not a diagnosis: It is a prediction of relative future risk compared to other people.” In other words, someone with BRCA1 has a higher risk than someone without, and someone with a high breast cancer PRS has a higher risk than someone with a lower breast cancer PRS. But in principle, BRCA1 is just one gene out of thousands contributing to a PRS, with each bit contributing a small part of a total risk estimate. ...
... Recently, a group of European scientists argued that polygenic screening should not be available to couples because it will lead to stigmatization, exacerbate inequalities, or lead to confusion by parents about how to weigh up information about risks before they decide which embryo to implant. These are indeed challenges, but they are not unique to embryo selection using polygenic scores, and they are not plausible arguments for restricting the autonomy of parents who wish to screen their embryos for polygenic traits. Furthermore, from an ethical perspective, it is unconscionable to deny polygenic screening to families with a history of any disease whose risk can be reduced by this lifesaving technology.
Many new technologies are initially only available to people with more money, but these first adopters then end up subsidizing research that drives costs down and quality up. Many other medical choices involve complexity or might result in some people being stigmatized, but this is a reason to encourage genetic counseling and to encourage social tolerance. It is not a reason to marginalize, stigmatize, or criminalize IVF mothers and fathers who wish to use the best available science to increase the chances that their children will be healthy and happy.
This is a comment on the article:
1) They don't want to admit that some people are better than others, inherently. Boo hoo.
2) You put a scorecard of embryos in front of everyone, and everyone has a pretty good ballpark estimate of which are better and which are worse. Nobody is going to pretend equality is true when they are choosing their kids genes.
3) So bad feels.
4) Must therefore retard all human progress and cause immense suffering because don't want to deal with bad feels.
That's the anti-polygenic argument in a nutshell. I don't expect it to be very effective. At best it will cause it to take a bit longer before poor people have access.
