China Smart, US Dumb: LLMs Bad, MoEs Good
November 21, 2024
Okay, an “MoE” is an alternative to LLMs. An “MoE” is a mixture of experts. An LLM is a one-trick pony starting to wheeze.
Google, Apple, Amazon, GitHub, OpenAI, Facebook, and other organizations are at the top of the list when people think about AI innovations. We forget about other countries and universities experimenting with the technology. Tencent is a China-based technology conglomerate located in Shenzhen and it’s the world’s largest video game company with equity investments are considered. Tencent is also the developer of Hunyuan-Large, the world’s largest MoE.
According to Tencent, LLMs (large language models) are things of the past. LLMs served their purpose to advance AI technology, but Tencent realized that it was necessary to optimize resource consumption while simultaneously maintaining high performance. That’s when the company turned to the next evolution of LLMs or MoE, mixture of experts models.
Cornell University’s open-access science archive posted this paper on the MoE: “Hunyuan-Large: An Open-Source MoE Model With 52 Billion Activated Parameters By Tencent” and the abstract explains it is a doozy of a model:
In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 billion activation parameters, capable of handling up to 256K tokens. We conduct a thorough evaluation of Hunyuan-Large’s superior performance across various benchmarks including language understanding and generation, logical reasoning, mathematical problem-solving, coding, long-context, and aggregated tasks, where it outperforms LLama3.1-70B and exhibits comparable performance when compared to the significantly larger LLama3.1-405B model. Key practice of Hunyuan-Large include large-scale synthetic data that is orders larger than in previous literature, a mixed expert routing strategy, a key-value cache compression technique, and an expert-specific learning rate strategy. Additionally, we also investigate the scaling laws and learning rate schedule of mixture of experts models, providing valuable insights and guidance for future model development and optimization. The code and checkpoints of Hunyuan-Large are released to facilitate future innovations and applications.”
Tencent has released Hunyuan-Large as an open source project, so other AI developers can use the technology! The well-known companies will definitely be experimenting with Hunyuan-Large. Is there an ulterior motive? Sure. Money, prestige, and power are at stake in the AI global game.
Whitney Grace, November 21, 2024
Meta and China: Yeah, Unauthorized Use of Llama. Meh
November 8, 2024
This post is the work of a dinobaby. If there is art, accept the reality of our using smart art generators. We view it as a form of amusement.
That open source smart software, you remember, makes everything computer- and information-centric so much better. One open source champion laboring as a marketer told me, “Open source means no more contractual handcuffs, the ability to make changes without a hassle, and evidence of the community.
An AI-powered robot enters a meeting. One savvy executive asks in Chinese, “How are you? Are you here to kill the enemy?” Another executive, seated closer to the gas emitted from a cannister marked with hazardous materials warnings gasps, “I can’t breathe!” Thanks, Midjourney. Good enough.
How did those assertions work for China? If I can believe the “trusted” outputs of the “real” news outfit Reuters, just super cool. “Exclusive: Chinese Researchers Develop AI Model for Military Use on Back of Meta’s Llama”, those engaging folk of the Middle Kingdom:
… have used Meta’s publicly available Llama model to develop an AI tool for potential military applications, according to three academic papers and analysts.
Now that’s community!
The write up wobbles through some words about the alleged Chinese efforts and adds:
Meta has embraced the open release of many of its AI models, including Llama. It imposes restrictions on their use, including a requirement that services with more than 700 million users seek a license from the company. Its terms also prohibit use of the models for “military, warfare, nuclear industries or applications, espionage” and other activities subject to U.S. defense export controls, as well as for the development of weapons and content intended to “incite and promote violence”. However, because Meta’s models are public, the company has limited ways of enforcing those provisions.
In the spirit of such comments as “Senator, thank you for that question,” a Meta (aka Facebook), wizard allegedly said:
“That’s a drop in the ocean compared to most of these models (that) are trained with trillions of tokens so … it really makes me question what do they actually achieve here in terms of different capabilities,” said Joelle Pineau, a vice president of AI Research at Meta and a professor of computer science at McGill University in Canada.
My interpretation of the insight? Hey, that’s okay.
As readers of this blog know, I am not too keen on making certain information public. Unlike some outfits’ essays, Beyond Search tries to address topics without providing information of a sensitive nature. For example, search and retrieval is a hard problem. Big whoop.
But posting what I would term sensitive information as usable software for anyone to download and use strikes me as something which must be considered in a larger context; for example, a bad actor downloading an allegedly harmless penetration testing utility of the Metasploit-ilk. Could a bad actor use these types of software to compromise a commercial or government system? The answer is, “Duh, absolutely.”
Meta’s founder of the super helpful Facebook wants to bring people together. Community. Kumbaya. Sharing.
That has been the lubricant for amassing power, fame, and money… Oh, also a big gold necklace similar to the one’s I saw labeled “Pharaoh jewelry.”
Observations:
- Meta (Facebook) does open source for one reason: To blunt initiatives from its perceived competitors and to position itself to make money.
- Users of Meta’s properties are only data inputters and action points; that is, they are instrumentals.
- Bad actors love that open source software. They download it. They study it. They repurpose it to help the bad actors achieve their goals.
Did Meta include a kill switch in its open source software? Oh, sure. Meta is far-sighted, concerned with misuse of its innovations, and super duper worried about what an adversary of the US might do with that technology. On the bright side, if negotiations are required, the head of Meta (Facebook) allegedly speaks Chinese. Is that a benefit? He could talk with the weaponized robot dispensing biological warfare agents.
Stephen E Arnold, November 8, 2024
Money and Open Source: Unpleasant Taste?
October 23, 2024
Open-source veteran and blogger Armin Ronacher ponders “The Inevitability of Mixing Open Source and Money.” It is lovely when developers work on open-source projects for free out of the goodness of their hearts. However, the truth is these folks can only afford to spend so much time working for free. (A major reason open source documentation is a mess, by the way.)
For his part, Ronacher helped launch Sentry’s Open Source Pledge. That initiative asks companies to pledge funding to open source projects they actively use. It is particularly focused on small projects, like xz, that have a tougher time attracting funds than the big names. He acknowledges the perils of mixing open source and money, as described by Word Press’s David Heinemeier Hansson. But he insists the blend is already baked in. He considers:
“At face value, this suggests that Open Source and money shouldn’t mix, and that the absence of monetary rewards fosters a unique creative process. There’s certainly truth to this, but in reality, Open Source and money often mix quickly. If you look under the cover of many successful Open Source projects you will find companies with their own commercial interests supporting them (eg: Linux via contributors), companies outright leading projects they are also commercializing (eg: MariaDB, redis) or companies funding Open Source projects primarily for marketing / up-sell purposes (uv, next.js, pydantic, …). Even when money doesn’t directly fund an Open Source project, others may still profit from it, yet often those are not the original creators. These dynamics create stresses and moral dilemmas.”
For example, the conflict between Hansson and WP Engine. The tension can also personal stress. Ronacher shares doubts that have plagued him: to monetize or not to monetize? Would a certain project have taken off had he poured his own money into it? He has watched colleagues wrestle with similar questions that affected their health and careers. See his post for more on those issues. The write-up concludes:
“I firmly believe that the current state of Open Source and money is inadequate, and we should strive for a better one. Will the Pledge help? I hope for some projects, but WordPress has shown that we need to drive forward that conversation of money and Open Source regardless of the size of the project.”
Clearly, further discussion is warranted. New ideas from open-source enthusiasts are also needed. Can a balance be found?
Cynthia Murrell, October 23, 2024
Open Source Versus Commercial Software. The Result? A Hybrid Which Neither Parent May Love
September 30, 2024
This essay is the work of a dumb dinobaby. No smart software required.
I have been down the open source trail a couple of times. The journey was pretty crazy because open source was software created to fulfill a computer science class requirement, a way to provide some “here’s what I can do” vibes to a résumé when résumés were anchored to someone’s reality, and “play” that would get code adopted so those in the know could sell services like engineering support, customizing, optimizing, and “making it mostly work.” In this fruit cake, were licenses, VCs, lone-wolves, and a few people creating something useful for a “community” which might or might not “support” the effort. Flip enough open source rocks and one finds some fascinating beasts like IBM, Microsoft, and other giant technology outfits.
Some hybrids work; others do not. Thanks, MSFT Copilot, good enough.
Today I learned their is now a hybrid of open source and proprietary (commercial) software. According to the “Some Startups Are Going Fair Source to Avoid the Pitfalls of Open Source Licensing” states:
The fair source concept is designed to help companies align themselves with the “open” software development sphere, without encroaching into existing licensing landscapes, be that open source, open core, or source-available, and while avoiding any negative associations that exist with “proprietary.” However, fair source is also a response to the growing sense that open source isn’t working out commercially.
Okay. I think “not working out commercially” is “real news” speak for “You can’t make enough money to become a Silicon Type mogul.” The write up adds:
Businesses that have flown the open source flag have mostly retreated to protect their hard work, moving either from fully permissive to a more restrictive “copyleft” license, as the likes of Element did last year and Grafana before it, or ditched open source altogether as HashiCorp did with Terraform.
These are significant developments. What about companies which have built substantial businesses surfing on open source software and have not been giving back in equal measure to the “community”? My hunch is that many start ups use the open source card as a way to get some marketing wind in their tiny sails. Other outfits just cobble together a number of open source software components and assemble a new and revolutionary product. The savings come from the expense of developing an original solution and using open source software to build what becomes a proprietary system. The origins of some software is either ignored by some firms or lost in the haze of employee turnover. After all, who remembers? A number of intelware companies which off specialized services to government agencies incorporate some open source software and use their low profile or operational secrecy to mask what their often expensive products provide to a government entity.
The write up notes:
For now, the main recommended fair source license is the Functional Source License (FSL), which Sentry itself launched last year as a simpler alternative to BUSL. However, BUSL itself has also now been designated fair source, as has another new Sentry-created license called the Fair Core License (FCL), both of which are included to support the needs of different projects. Companies are welcome to submit their own license for consideration, though all fair source licenses should have three core stipulations: It [the code] should be publicly available to read; allow third parties to use, modify, and redistribute with “minimal restrictions“; and have a delayed open source publication (DOSP) stipulation, meaning it converts to a true open source license after a predefined period of time. With Sentry’s FSL license, that period is two years; for BUSL, the default period is four years. The concept of “delaying” publication of source code under a true open source license is a key defining element of a fair source license, separating it from other models such as open core. The DOSP protects a company’s commercial interests in the short term, before the code becomes fully open source.
My reaction is that lawyers will delight in litigating such notions as “minimal restrictions.” The cited article correctly in my opinion says:
Much is open to interpretation and can be “legally fuzzy.”
Is a revolution in software licensing underway?
Some hybrids live; others die.
Stephen E Arnold, September 30, 2024
Open Source Dox Chaos: An Opportunity for AI
September 24, 2024
It is a problem as old as the concept of open source itself. ZDNet laments, “Linux and Open-Source Documentation Is a Mess: Here’s the Solution.” We won’t leave you in suspense. Writer Steven Vaughan-Nichols’ solution is the obvious one—pay people to write and organize good documentation. Less obvious is who will foot the bill. Generous donors? Governments? Corporations with their own agendas? That question is left unanswered.
But there is not doubt. Open-source documentation, when it exists at all, is almost universally bad. Vaughan-Nichols recounts:
“When I was a wet-behind-the-ears Unix user and programmer, the go-to response to any tech question was RTFM, which stands for ‘Read the F… Fine Manual.’ Unfortunately, this hasn’t changed for the Linux and open-source software generations. It’s high time we addressed this issue and brought about positive change. The manuals and almost all the documentation are often outdated, sometimes nearly impossible to read, and sometimes, they don’t even exist.”
Not only are the manuals that have been cobbled together outdated and hard to read, they are often so disorganized it is hard to find what one is looking for. Even when it is there. Somewhere. The post emphasizes:
“It doesn’t help any that kernel documentation consists of ‘thousands of individual documents’ written in isolation rather than a coherent body of documentation. While efforts have been made to organize documents into books for specific readers, the overall documentation still lacks a unified structure. Steve Rostedt, a Google software engineer and Linux kernel developer, would agree. At last year’s Linux Plumbers conference, he said, ‘when he runs into bugs, he can’t find documents describing how things work.’ If someone as senior as Rostedt has trouble, how much luck do you think a novice programmer will have trying to find an answer to a difficult question?”
This problem is no secret in the open-source community. Many feel so strongly about it they spend hours of unpaid time working to address it. Until they just cannot take it anymore. It is easy to get burned out when one is barely making a dent and no one appreciates the effort. At least, not enough to pay for it.
Here at Beyond Search we have a question: Why can’t Microsoft’s vaunted Copilot tackle this information problem? Maybe Copilot cannot do the job?
Cynthia Murrell, September 24, 2024
Is Open Source Doomed?
September 6, 2024
Open source cheerleaders may need to find a new team to route for. Web developer and blogger Baldur Bjarnason describes “The Slow Evaporation of the Free/Open Source Surplus.” He notes he is joining a conversation begun by Tara Tarakiyee with the post, Is the Open Source Bubble about to Burst? and continued by Ben Werdmuller.
Bjarnason begins by specifying what has made open source software possible up until now: surpluses in both industry (high profit margins) and labor (well-paid coders with plenty of free time.) Now, however, both surpluses are drying up. The post lists several reasons for this. First, interest rates remain high. Next, investment dollars are going to AI, which “doesn’t really do real open source.” There were also the waves of tech layoffs and cost-cutting after post-pandemic overspending. Severe burnout from a thankless task does not help. We are reminded:
“Very few FOSS projects are lucky enough to have grown a sustainable and supportive community. Most of the time, it seems to be a never-ending parade of angry demands with very little reward.”
Good point. A few other factors, Bjarnason states, make organizations less likely to invest in open source:
- Why compete with AWS or similar services that will offer your own OSS projects at a dramatically lower price?
- Why subsidise projects of little to no strategic value that contribute anything meaningfully to the bottom-line?
- Why spend time on OSS when other work is likely to have higher ROI?
- Why give your work away to an industry that treats you as disposable?”
Finally, Bjarnason suspects even users are abandoning open source. One factor: developers who increasingly reach for AI generated code instead of searching for related open source projects. Ironically, those LLMs were trained on open source software in the first place. The post concludes:
Best case scenario, seems to me, is that Free and Open Source Software enters a period of decline. After all, that’s generally what happens to complex systems with less investment. Worst case scenario is a vicious cycle leading to a collapse:
- Declining surplus and burnout leads to maintainers increasingly stepping back from their projects.
- Many of these projects either bitrot serious bugs or get taken over by malicious actors who are highly motivated because they can’t relay on pervasive memory bugs anymore for exploits.
- OSS increasingly gets a reputation (deserved or not) for being unsafe and unreliable.
- That decline in users leads to even more maintainers stepping back.”
Bjarnason notes it is possible some parts of the Open Source ecosystem will not crash and burn. Overall, though, the outlook seems bleak.
Cynthia Murrell, September 6, 2024
The Big Battle: Another WWF Show Piece for AI
August 2, 2024
This essay is the work of a dumb humanoid. No smart software required.
The Zuck believes in open source. It is like Linux. Boom. Market share. OpenAI believes in closed source (for now). Snap. You have to pay to get the good stuff. The argument about proprietary versus open source has been plodding along like Russia’s special operation for a long time. A typical response, in my opinion, is that open source is great because it allows a corporate interest to get cheap traction. Then with a surgical or not-so-surgical move, the big outfit co-opts the open source project. Boom. Semi-open source with a price tag becomes a competitive advantage. Proprietary software can be given away, licensed, or made available by subscription. Open source creates opportunities for training, special services, and feeling good about the community. But in the modern world of high-technology feeling good comes with sustainable flows of revenue and opportunities to raise prices faster than the local grocery store.
Where does open source software come from? Many students demonstrate their value by coding something useful to another. Thanks, Open AI. Good enough.
I read “Consider the Llama: Are Closed Source AI Models Doomed?” The write up is good. It contains a passage which struck me as interesting; to wit:
OpenAI, Anthropic and the like—companies that sell access to AI models. These companies inherently require their products to be much better than open source in order to up-charge. They also don’t have some other product they sell that gets improved with better AI overall.
In my opinion, in the present business climate, the hope that a high-technology product gets better is an interesting one. The idea of continual improvement, however, is not part of the business culture of high-technology companies engaged in smart software. At this time, cooking up a model which can be used to streamline or otherwise enhance an existing activity is Job One. The first outfit to generate substantial revenue from artificial intelligence will have an advantage. That doesn’t mean the outfit won’t fail, but if one considers the requirements to play with a reasonable probability of winning the AI game, smart software costs money.
In the world of online, a company or open source foundation which delivers a product or service which attracts large numbers of users has an advantage. One “play” can shift the playing field, not just win the game. What’s going on at this time, in my opinion, is that those who understand the advantage of winning in the equivalent of a WWF (World Wide Wrestling) show piece is that it allows the “winner take all” or at least the “winner takes two-thirds” of the market.
Monopolies (real or imagined) with lots of money have an advantage. Open source smart software have to have money from somewhere; otherwise, the costs of producing a winning service drop. If a large outfit with cash goes open source, that is a bold chess move which other outfits cannot afford to take. The feel good, community aspect of a smart software solution that can be used in a large number of use cases is going to fade quickly when any money on the table is taken by users who neither contribute, pay for training, or hire great open source coders as consultants. Serious players just take the software, innovate, and lock up the benefits.
“Who would do this?” some might ask.
How about China, Russia, or some nation state not too interested in the Silicon Valley way? How about an entrepreneur in Armenia or one of the Stans who wants to create a novel product or service and charge for it? Sure, US-based services may host the product or service, but the actual big bucks flow to the outfit who keeps the technology “secret”?
At this time, US companies which make high-value software available for free to anyone who can connect to the Internet and download a file are not helping American business. You may disagree. But I know that there are quite a few organizations (commercial and governmental) who think the US approach to open source software is just plain dumb.
Wrapping up an important technology with do-goodism and mostly faux hand waving about the community creates two things:
- An advantage for commercial enterprises who want to thwart American technical influence
- Free intelligence for nation-states who would like nothing more than convert the US into a client republic.
I did a job for a bunch of venture people who were into the open source religion. The reality is that at this time an alleged monopoly like Google can use its money and control of information flows to cripple other outfits trying to train their systems. On the other hand, companies who just want AI to work may become captive to an enterprise software vendor who is also an alleged monopoly. The companies funded by this firm have little chance of producing sustainable revenue. The best exits will be gift wrapping the “innovation” and selling it to another group of smart software-hungry investors.
Does the world need dozens of smart software “big dogs”? The answer is, “No.” At this time, the US is encouraging companies to make great strides in smart software. These are taking place. However, the rest of the world is learning and may have little or no desire to follow the open source path to the big WWF face off in the US.
The smart software revolution is one example of how America’s technology policy does not operate in a way that will cause our adversaries to do anything but download, enhance, build on, and lock up increasingly smarter AI systems.
From my vantage point, it is too late to undo the damage the wildness of the last few years can be remediated. The big winners in open source are not the individual products. Like the WWF shows, the winner is the promoter. Very American and decidedly different from what those in other countries might expect or want. Money, control, and power are more important than the open source movement. Proprietary may be that group’s preferred approach. Open source is software created by computer science students to prove they can produce code that does something. The “real” smart software is quite different.
Stephen E Arnold, August 2, 2024
Another Open Source AI Voice Speaks: Yo, Meta!
July 3, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
The open source software versus closed source software demonstrates ebbs and flows. Like the “go fast” with AI and “go slow” with AI, strong opinions suggest that big money and power are swirling like the storms on a weather app for Oklahoma in tornado season. The most recent EF5 is captured in “Zuckerberg Disses Closed-Source AI Competitors As Trying to Create God.” The US government seems to be concerned about open source smart software finding its way into the hands of those who are not fans of George Washington-type thinking.
Which AI philosophy will win the big pile of money? Team Blue representing the Zuck? Or, the rag tag proprietary wizards? Thanks, MSFT Copilot. You are into proprietary, aren’t you?
The “move fast and break things” personage of Mark Zuckerberg is into open source smart software. In the write up, he allegedly said in a YouTube bit:
“I don’t think that AI technology is a thing that should be kind of hoarded and … that one company gets to use it to build whatever central, single product that they’re building,” Zuckerberg said in a new YouTube interview with Kane Sutter (@Kallaway).
The write up includes this passage:
In the conversation, Zuckerberg said there needs to be a lot of different AIs that get created to reflect people’s different interests.
One interesting item in the article, in my opinion, is this:
“You want to unlock and … unleash as many people as possible trying out different things,” he continued. “I mean, that’s what culture is, right? It’s not like one group of people getting to dictate everything for people.”
But the killer Meta vision is captured in this passage:
Zuckerberg said there will be three different products ahead of convergence: display-less smart glasses, a heads-up type of display and full holographic displays. Eventually, he said that instead of neural interfaces connected to their brain, people might one day wear a wristband that picks up signals from the brain communicating with their hand. This would allow them to communicate with the neural interface by barely moving their hand. Over time, it could allow people to type, too. Zuckerberg cautioned that these types of inputs and AI experiences may not immediately replace smartphones, though. “I don’t think, in the history of technology, the new platform — it usually doesn’t completely make it that people stop using the old thing. It’s just that you use it less,” he said.
In short, the mobile phone is going down, not tomorrow, but definitely to the junk drawer.
Several observations which I know you are panting to read:
- Never under estimate making something small or re-invented as a different form factor. The Zuck might be “right.”
- The idea of “unleash” is interesting. What happens if employees at WhatsApp unleash themselves? How will the Zuck construct react? Like the Google? Something new like blue chip consulting firms replacing people with smart software? “Unleash” can be interpreted in different ways, but I am thinking of turning loose a pack of hyenas. The Zuck may be thinking about eager kindergartners. Who knows?
- The Zuck’s position is different from the government officials who are moving toward restrictions on “free and open” smart software. Those hallucinating large language models can be repurposed into smart weapons. Close enough for horseshoes with enough RDX may do the job.
Net net: The Zuck is an influential and very powerful information channel owner. “Unleash” what? Hungry predators or those innovating children? Perhaps neither. But as OpenAI seems to be closing; the Zuck AI is into opening. Ah, uncertainty is unfolding before my eyes in real time.
Stephen E Arnold, July 3, 2024
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OpenAI: Do You Know What Open Means? Does Anyone?
July 1, 2024
This essay is the work of a dumb dinobaby. No smart software required.
The backstory for OpenAI was the concept of “open.” Well, the meaning of “open” has undergone some modification. There was a Musk up, a board coup, an Apple announcement that was vaporous, and now we arrive at the word “open” as in “OpenAI.”
Open source AI is like a barn that burned down. Hopefully the companies losing their software’s value have insurance. Once the barn is gone, those valuable animals may be gone. Thanks, MSFT Copilot. Good enough. How’s that Windows update going this week?
“OpenAI Taking Steps to Block China’s Access to Its AI Tools” reports with the same authority Bloomberg used with its “your motherboard is phoning home” crusade a few years ago [Note: If the link doesn’t render, search Bloomberg for the original story]:
OpenAI is taking additional steps to curb China’s access to artificial intelligence software, enforcing an existing policy to block users in nations outside of the territory it supports. The Microsoft Corp.-backed startup sent memos to developers in China about plans to begin blocking their access to its tools and software from July, according to screenshots posted on social media that outlets including the Securities Times reported on Tuesday. In China, local players including Alibaba Group Holding Ltd. and Tencent Holdings Ltd.-backed Zhipu AI posted notices encouraging developers to switch to their own products.
Let’s assume the information in the cited article is on the money. Yes, I know this is risky today, but do you know an 80-year-old who is not into thrills and spills?
According to Claude 3.5 Sonnet (which my team is testing), “open” means:
Not closed or fastened
Accessible or available
Willing to consider or receive
Exposed or vulnerable
The Bloomberg article includes this passage:
OpenAI supports access to its services in dozens of countries. Those accessing its products in countries not included on the list, such as China, may have their accounts blocked or suspended, according to the company’s guidelines. It’s unclear what prompted the move by OpenAI. In May, Sam Altman’s startup revealed it had cut off at least five covert influence operations in past months, saying they were using its products to manipulate public opinion.
I found this “real” news interesting:
From Baidu Inc. to startups like Zhipu, Chinese firms are trying to develop AI models that can match ChatGPT and other US industry pioneers. Beijing is openly encouraging local firms to innovate in AI, a technology it considers crucial to shoring up China’s economic and military standing.
It seems to me that “open” means closed.
Another angle surfaces in the Nature Magazine’s article “Not All Open Source AI Models Are Actually Open: Here’s a Ranking.” OpenAI is not alone in doing some linguistic shaping with the word “open.” The Nature article states:
Technology giants such as Meta and Microsoft are describing their artificial intelligence (AI) models as ‘open source’ while failing to disclose important information about the underlying technology, say researchers who analysed a host of popular chatbot models. The definition of open source when it comes to AI models is not yet agreed, but advocates say that ’full’ openness boosts science, and is crucial for efforts to make AI accountable.
Now this sure sounds to me as if the European Union is defining “open” as different from the “open” of OpenAI.
Let’s step back.
Years ago I wrote a monograph about open source search. At that time IDC was undergoing what might charitably be called “turmoil.” Chapters of my monograph were published by IDC on Amazon. I recycled the material for consulting engagements, but I learned three useful things in the research for that analysis of open source search systems:
- Those making open source search systems available at free and open source software wanted the software [a] to prove their programming abilities, [b] to be a foil for a financial play best embodied in the Elastic go-public and sell services “play”; [c] be a low-cost, no-barrier runway to locking in users; that is, a big company funds the open source software and has a way to make money every which way from the “free” bait.
- Open source software is a product testing and proof-of-concept for developers who are without a job or who are working in a programming course in a university. I witnessed this approach when I lectured in Tallinn, Estonia, in the 2000s. The “maybe this will stick” approach yields some benefits, primarily to the big outfits who co-opt an open source project and support it. When the original developer gives up or gets a job, the big outfit has its hands on the controls. Please, see [c] in item 1 above.
- Open source was a baby buzzword when I was working on my open source search research project. Now “open source” is a full-scale, AI-jargonized road map to making money.
The current mix up in the meaning of “open” is a direct result of people wearing suits realizing that software has knowledge value. Giving value away for nothing is not smart. Hence, the US government wants to stop its nemesis from having access to open source software, specifically AI. Big companies do not want proprietary knowledge to escape unless someone pays for the beast. Individual developers want to get some fungible reward for creating “free” software. Begging for dollars, offering a disabled version of software or crippleware, or charging for engineering “support” are popular ways to move from free to ka-ching. Big companies have another angle: Lock in. Some outfits are inept like IBM’s fancy dancing with Red Hat. Other companies are more clever; for instance, Microsoft and its partners and AI investments which allow “open” to become closed thank you very much.
Like many eddies in the flow of the technology river, change is continuous. When someone says, “Open”, keep in mind that thing may be closed and have a price tag or handcuffs.
Net net: The AI secrets have flown the coop. It has taken about 50 years to reach peak AI. The new angles revealed in the last year are not heart stoppers. That smoking ruin over there. That’s the locked barn that burned down. Animals are gone or “transformed.”
Stephen E Arnold, July 1, 2024
Open Source Drone Mapping Software
May 30, 2024
This essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.
Photography and 3D image rendering aren’t perfect technologies, but they’ve dramatically advanced since they became readily available. Photorealistic 3D rendering was only available to the ultra wealthy, corporations, law enforcement agencies, universities, and governments. The final products were laughable by today’s standards, but it set the foundation for technology like Open Drone Map.
OpenDroneMap is a cartographer’s dream software that generates, 3D models, digital elevation models, point clouds, and maps from aerial images. Using only a compatible drone, the software, and a little programming know-how, users can make maps that were once the domain of specific industries. The map types include: measurements, plant health, point clouds, orthomosaics, contours (topography), elevation models, ground point controls, and more.
OpenDroneMap is self-described as: “We are creating the most sustainable drone mapping software with the friendliest community on earth.” It’s also called an “open ecosystem:”
“We’re building sustainable solutions for collecting, processing, analyzing and displaying aerial data while supporting the communities built around them. Our efforts are made possible by collaborations with key organizations, individuals and with the help of our growing community.”
The software is run by a board consisting of: Imma Mwanza, Stephen Mather, Näiké Nembetwa Nzali, DK Benjamin, and Arun M. The rest of the “staff” are contributors to the various projects, mostly through GitHub.
There are many projects that are combined for the complete OpenDroneMap software. These projects include: the command line toolkit, user interface, GCP detection, Python SDK, and more. Users can contribute by helping design code and financial donations. OpenDroneMap is a nonprofit, but it has the potential to be a company.
Open source projects like, OpenDroneMap, are how technology should be designed and deployed. The goal behind OpenDroneMap is to create a professional, decisive, and used for good.
Whitney Grace, May 30, 2024
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